Champions: 1991, 1992, 1993, 1996, 1997, 1998 Conference Titles: 1991, 1992, 1993, 1996, 1997, 1998 Division Titles: 1975, 1991, 1992, 1993, 1996, 1997, 1998, 2011, 2012

Champions: 1991, 1992, 1993, 1996, 1997, 1998
Conference Titles: 1991, 1992, 1993, 1996, 1997, 1998
Division Titles: 1975, 1991, 1992, 1993, 1996, 1997, 1998, 2011, 2012

Overview

This assessment task allows you to consolidate and apply the concepts and skills you’ve learnt throughout the semester. This assessment requires you to generate a reproducible data analysis project.

Your reproducible data analysis project will be hosted as a repository on GitHub and you are required to submit the URL to your GitHub repository.

Scenario and Aim of the Data Analysis Project

You are a data analyst with the Chicago Bulls competing in the NBA (national basketball association). In the most recent NBA season (2018-19), your team placed 27th out of 30 (for win-loss record). Your team’s budget for player contracts next season is $118 million, ranked 26th out of 30 (for the purpose of this assignment, next season is 2019-20). For context, the team with the highest payroll budget is Portland with $148 million, while the best performing team was Milwaukee Bucks (who clinched the best league record in 2018-19 who clinched the best league record in 2018-29) with $131 million.

You have been tasked by the general manager of Chicago Bulls to find the best five starting players one from each position) your team can afford. (Make sure you don’t use up all of your money on just these five players, you still need to fill a full team roster, but are just focussed on finding five starting players here). You can choose players that are already playing for Chicago Bulls, you just need to prove that they are worth it.

Load required packages

## ── Attaching packages ───────────────────────────────────────────────────── tidyverse 1.3.0 ──
## ✓ ggplot2 3.3.0     ✓ purrr   0.3.4
## ✓ tibble  3.0.1     ✓ dplyr   0.8.5
## ✓ tidyr   1.1.0     ✓ stringr 1.4.0
## ✓ readr   1.3.1     ✓ forcats 0.5.0
## ── Conflicts ──────────────────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()
## 
## Attaching package: 'kableExtra'
## The following object is masked from 'package:dplyr':
## 
##     group_rows
## 
## Attaching package: 'magrittr'
## The following object is masked from 'package:purrr':
## 
##     set_names
## The following object is masked from 'package:tidyr':
## 
##     extract

Data source

We have been provided the following data sets: 1. 2018-19_nba_player-statistics.csv : sourced from basketball-reference.com

  1. 2018-19_nba_player-salaries.csv : sourced from hoopshype.com/salaries

  2. 2019-20_nba_team-payroll.csv : sourced from hoopshype.com/salaries

  3. 2018-19_nba_team-statistics_1.csv : sourced from basketball-reference.com

  4. 2018-19_nba_team-statistics_2.csv : sourced from basketball-reference.com

Read Data (Correct)

Read in the various files using the read_csv() function from the readr package.

## Parsed with column specification:
## cols(
##   .default = col_double(),
##   player_name = col_character(),
##   Pos = col_character(),
##   Tm = col_character()
## )
## See spec(...) for full column specifications.
## Warning: Missing column names filled in: 'X4' [4], 'X5' [5], 'X6' [6], 'X7' [7]
## Parsed with column specification:
## cols(
##   player_id = col_double(),
##   player_name = col_character(),
##   salary = col_double(),
##   X4 = col_logical(),
##   X5 = col_logical(),
##   X6 = col_logical(),
##   X7 = col_logical()
## )
## Warning: Missing column names filled in: 'X23' [23], 'X24' [24], 'X25' [25]
## Parsed with column specification:
## cols(
##   .default = col_double(),
##   Team = col_character(),
##   X23 = col_logical(),
##   X24 = col_logical(),
##   X25 = col_logical()
## )
## See spec(...) for full column specifications.
## Parsed with column specification:
## cols(
##   .default = col_double(),
##   Team = col_character()
## )
## See spec(...) for full column specifications.
## Parsed with column specification:
## cols(
##   team_id = col_double(),
##   team = col_character(),
##   salary = col_character()
## )

Dealing with NAs

## Warning: funs() is soft deprecated as of dplyr 0.8.0
## Please use a list of either functions or lambdas: 
## 
##   # Simple named list: 
##   list(mean = mean, median = median)
## 
##   # Auto named with `tibble::lst()`: 
##   tibble::lst(mean, median)
## 
##   # Using lambdas
##   list(~ mean(., trim = .2), ~ median(., na.rm = TRUE))
## This warning is displayed once per session.

Transforming the Data

New variables

## `mutate_if()` ignored the following grouping variables:
## Column `Pos`
player_name Pos Age Tm Salary G GS MP FG FGA FGp x3P x3PA x3Pp x2P x2PA x2Pp eFGp FT FTA FTp ORB DRB TRB AST STL BLK TOV PF PTS PTSpm FTpm BLKpm ASTpm STLpm TOVpm x3Ppm PPG APG RPG
Al Horford C 32 BOS 28928710 68 68 1973 387 723 0.535 73 203 0.360 314 520 0.604 0.586 78 95 0.821 120 338 458 283 59 86 102 126 925 0.469 0.040 0.044 0.143 0.030 0.052 0.037 13.603 4.162 6.735
Alex Len C 25 ATL 4350000 77 31 1544 320 648 0.494 74 204 0.363 246 444 0.554 0.551 140 216 0.648 158 266 424 86 27 69 97 200 854 0.553 0.091 0.045 0.056 0.017 0.063 0.048 11.091 1.117 5.506
Amir Johnson C 31 PHI 2393887 51 6 529 79 157 0.503 12 40 0.300 67 117 0.573 0.541 31 41 0.756 47 100 147 60 16 13 45 99 201 0.380 0.059 0.025 0.113 0.030 0.085 0.023 3.941 1.176 2.882
Andre Drummond C 25 DET 25434262 79 79 2647 561 1052 0.533 5 38 0.132 556 1014 0.548 0.536 243 412 0.590 423 809 1232 112 136 138 175 272 1370 0.518 0.092 0.052 0.042 0.051 0.066 0.002 17.342 1.418 15.595
Anthony Davis C 25 NOP 25434263 56 56 1850 530 1026 0.517 48 145 0.331 482 881 0.547 0.540 344 433 0.794 174 498 672 218 88 135 112 132 1452 0.785 0.186 0.073 0.118 0.048 0.061 0.026 25.929 3.893 12.000
Aron Baynes C 32 BOS 5193600 51 18 821 105 223 0.471 21 61 0.344 84 162 0.519 0.518 53 62 0.855 88 152 240 57 12 34 40 125 284 0.346 0.065 0.041 0.069 0.015 0.049 0.026 5.569 1.118 4.706
Bam Adebayo C 21 MIA 2955840 82 28 1913 280 486 0.576 3 15 0.200 277 471 0.588 0.579 166 226 0.735 165 432 597 184 71 65 121 203 729 0.381 0.087 0.034 0.096 0.037 0.063 0.002 8.890 2.244 7.280
Bismack Biyombo C 26 CHO 17000000 54 32 783 89 156 0.571 0 0 0.000 89 156 0.571 0.571 58 91 0.637 81 166 247 33 11 41 34 103 236 0.301 0.074 0.052 0.042 0.014 0.043 0.000 4.370 0.611 4.574
Brook Lopez C 30 MIL 3382000 81 81 2322 355 786 0.452 187 512 0.365 168 274 0.613 0.571 112 133 0.842 33 363 396 98 51 179 82 189 1009 0.435 0.048 0.077 0.042 0.022 0.035 0.081 12.457 1.210 4.889
Channing Frye C 35 CLE 2393887 36 6 341 43 117 0.368 32 79 0.405 11 38 0.289 0.504 11 14 0.786 4 48 52 20 6 5 13 44 129 0.378 0.032 0.015 0.059 0.018 0.038 0.094 3.583 0.556 1.444
Clint Capela C 24 HOU 15793104 67 67 2249 474 732 0.648 0 0 0.000 474 732 0.648 0.648 166 261 0.636 298 550 848 96 44 102 94 168 1114 0.495 0.074 0.045 0.043 0.020 0.042 0.000 16.627 1.433 12.657
Cody Zeller C 26 CHO 13528090 49 47 1243 190 345 0.551 6 22 0.273 184 323 0.570 0.559 111 141 0.787 110 223 333 102 38 41 62 164 497 0.400 0.089 0.033 0.082 0.031 0.050 0.005 10.143 2.082 6.796
Damian Jones C 23 GSW 1544951 24 22 410 53 74 0.716 0 0 0.000 53 74 0.716 0.716 24 37 0.649 31 44 75 28 12 25 16 63 130 0.317 0.059 0.061 0.068 0.029 0.039 0.000 5.417 1.167 3.125
Daniel Theis C 26 BOS 1378242 66 2 908 146 266 0.549 26 67 0.388 120 199 0.603 0.598 56 76 0.737 87 138 225 68 21 42 33 161 374 0.412 0.062 0.046 0.075 0.023 0.036 0.029 5.667 1.030 3.409
Deandre Ayton C 20 PHO 8175840 71 70 2183 509 870 0.585 0 4 0.000 509 866 0.588 0.585 141 189 0.746 223 506 729 125 61 67 126 209 1159 0.531 0.065 0.031 0.057 0.028 0.058 0.000 16.324 1.761 10.268
DeAndre Jordan C 30 TOT 22897200 69 69 2047 286 446 0.641 0 0 0.000 286 446 0.641 0.641 186 264 0.705 225 677 902 156 42 73 153 167 758 0.370 0.091 0.036 0.076 0.021 0.075 0.000 10.986 2.261 13.072
DeMarcus Cousins C 28 GSW 5337000 30 30 771 178 371 0.480 26 95 0.274 152 276 0.551 0.515 106 144 0.736 43 204 247 107 40 44 72 109 488 0.633 0.137 0.057 0.139 0.052 0.093 0.034 16.267 3.567 8.233
Derrick Favors C 27 UTA 16900000 76 70 1766 363 619 0.586 17 78 0.218 346 541 0.640 0.600 154 228 0.675 207 353 560 89 56 106 84 163 897 0.508 0.087 0.060 0.050 0.032 0.048 0.010 11.803 1.171 7.368
Dewayne Dedmon C 29 ATL 6300000 64 52 1609 259 526 0.492 83 217 0.382 176 309 0.570 0.571 92 113 0.814 105 375 480 90 69 71 84 214 693 0.431 0.057 0.044 0.056 0.043 0.052 0.052 10.828 1.406 7.500
Domantas Sabonis C 22 IND 2659800 74 5 1838 413 700 0.590 9 17 0.529 404 683 0.592 0.596 208 291 0.715 186 504 690 212 48 30 160 239 1043 0.567 0.113 0.016 0.115 0.026 0.087 0.005 14.095 2.865 9.324
Dwight Powell C 27 DAL 9631250 77 22 1662 290 486 0.597 39 127 0.307 251 359 0.699 0.637 196 254 0.772 140 271 411 112 44 50 67 201 815 0.490 0.118 0.030 0.067 0.026 0.040 0.023 10.584 1.455 5.338
Ed Davis C 29 BRK 4449000 81 1 1446 186 302 0.616 0 2 0.000 186 300 0.620 0.616 100 162 0.617 216 478 694 61 35 33 64 226 472 0.326 0.069 0.023 0.042 0.024 0.044 0.000 5.827 0.753 8.568
Ekpe Udoh C 31 UTA 3360000 51 1 320 50 72 0.694 0 0 0.000 50 72 0.694 0.694 19 30 0.633 27 63 90 28 10 31 13 36 119 0.372 0.059 0.097 0.088 0.031 0.041 0.000 2.333 0.549 1.765
Enes Kanter C 26 TOT 19264603 67 31 1640 375 683 0.549 10 34 0.294 365 649 0.562 0.556 155 197 0.787 257 402 659 116 32 26 118 167 915 0.558 0.095 0.016 0.071 0.020 0.072 0.006 13.657 1.731 9.836
Frank Kaminsky C 25 CHO 3627842 47 0 755 138 298 0.463 50 139 0.360 88 159 0.553 0.547 79 107 0.738 39 124 163 63 12 12 41 68 405 0.536 0.105 0.016 0.083 0.016 0.054 0.066 8.617 1.340 3.468
Gorgui Dieng C 29 MIN 15170787 76 2 1031 189 377 0.501 19 56 0.339 170 321 0.530 0.527 88 106 0.830 81 230 311 72 48 41 57 134 485 0.470 0.085 0.040 0.070 0.047 0.055 0.018 6.382 0.947 4.092
Greg Monroe C 28 TOT 2410167 43 2 480 92 189 0.487 1 5 0.200 91 184 0.495 0.489 45 72 0.625 67 105 172 24 14 8 32 66 230 0.479 0.094 0.017 0.050 0.029 0.067 0.002 5.349 0.558 4.000
Hassan Whiteside C 29 MIA 24434262 72 53 1674 388 680 0.571 2 16 0.125 386 664 0.581 0.572 109 243 0.449 257 560 817 56 46 136 97 192 887 0.530 0.065 0.081 0.033 0.027 0.058 0.001 12.319 0.778 11.347
Ian Mahinmi C 32 WAS 16000000 34 6 498 47 104 0.452 3 16 0.188 44 88 0.500 0.466 42 61 0.689 48 80 128 25 25 16 21 84 139 0.279 0.084 0.032 0.050 0.050 0.042 0.006 4.088 0.735 3.765
Ivica Zubac C 21 TOT 1544951 59 37 1040 212 379 0.559 0 0 0.000 212 379 0.559 0.559 101 126 0.802 115 247 362 63 14 51 70 137 525 0.505 0.097 0.049 0.061 0.013 0.067 0.000 8.898 1.068 6.136
Jahlil Okafor C 23 NOP 1567007 59 24 935 212 362 0.586 1 5 0.200 211 357 0.591 0.587 59 89 0.663 82 196 278 40 15 40 52 96 484 0.518 0.063 0.043 0.043 0.016 0.056 0.001 8.203 0.678 4.712
Jarrett Allen C 20 BRK 2034120 80 80 2096 335 568 0.590 6 45 0.133 329 523 0.629 0.595 197 278 0.709 191 481 672 110 43 120 103 184 873 0.417 0.094 0.057 0.052 0.021 0.049 0.003 10.912 1.375 8.400
JaVale McGee C 31 LAL 2393887 75 62 1671 400 641 0.624 1 12 0.083 399 629 0.634 0.625 96 152 0.632 195 371 566 52 47 148 108 208 897 0.537 0.057 0.089 0.031 0.028 0.065 0.001 11.960 0.693 7.547
Joakim Noah C 33 MEM 20261172 42 1 693 110 213 0.516 0 1 0.000 110 212 0.519 0.516 78 109 0.716 58 180 238 89 20 31 50 96 298 0.430 0.113 0.045 0.128 0.029 0.072 0.000 7.095 2.119 5.667
Joel Embiid C 24 PHI 25467250 64 64 2154 580 1199 0.484 79 263 0.300 501 936 0.535 0.517 522 649 0.804 160 711 871 234 46 122 226 211 1761 0.818 0.242 0.057 0.109 0.021 0.105 0.037 27.516 3.656 13.609
Johnathan Williams C 23 LAL 127250 24 0 372 65 110 0.591 0 2 0.000 65 108 0.602 0.591 27 48 0.563 48 51 99 13 8 7 16 62 157 0.422 0.073 0.019 0.035 0.022 0.043 0.000 6.542 0.542 4.125
Jordan Bell C 24 GSW 1378242 68 3 788 99 192 0.516 0 2 0.000 99 190 0.521 0.516 25 41 0.610 55 129 184 76 20 51 42 80 223 0.283 0.032 0.065 0.096 0.025 0.053 0.000 3.279 1.118 2.706
Karl-Anthony Towns C 23 MIN 7839435 77 77 2545 681 1314 0.518 142 355 0.400 539 959 0.562 0.572 376 450 0.836 263 691 954 259 67 125 240 292 1880 0.739 0.148 0.049 0.102 0.026 0.094 0.056 24.416 3.364 12.390
Kenneth Faried C 29 TOT 14242782 37 13 728 156 265 0.589 8 25 0.320 148 240 0.617 0.604 64 99 0.646 97 153 250 20 17 23 33 82 384 0.527 0.088 0.032 0.027 0.023 0.045 0.011 10.378 0.541 6.757
Kevon Looney C 22 GSW 1567007 80 24 1481 217 347 0.625 1 10 0.100 216 337 0.641 0.627 65 105 0.619 194 223 417 123 46 53 51 211 500 0.338 0.044 0.036 0.083 0.031 0.034 0.001 6.250 1.538 5.213
Khem Birch C 26 ORL 1378242 50 1 643 91 151 0.603 0 1 0.000 91 150 0.607 0.603 58 83 0.699 79 111 190 38 18 29 20 72 240 0.373 0.090 0.045 0.059 0.028 0.031 0.000 4.800 0.760 3.800
Kosta Koufos C 29 SAC 8739500 42 1 502 73 153 0.477 0 0 0.000 73 153 0.477 0.477 10 24 0.417 52 125 177 36 15 18 27 68 156 0.311 0.020 0.036 0.072 0.030 0.054 0.000 3.714 0.857 4.214
Kyle O’Quinn C 28 IND 4449000 45 3 371 69 136 0.507 1 12 0.083 68 124 0.548 0.511 17 21 0.810 29 90 119 56 9 25 31 68 156 0.420 0.046 0.067 0.151 0.024 0.084 0.003 3.467 1.244 2.644
LaMarcus Aldridge C 33 SAS 22347015 81 81 2687 684 1319 0.519 10 42 0.238 674 1277 0.528 0.522 349 412 0.847 251 493 744 194 43 107 144 179 1727 0.643 0.130 0.040 0.072 0.016 0.054 0.004 21.321 2.395 9.185
Larry Nance C 26 CLE 2272390 67 30 1795 249 479 0.520 33 98 0.337 216 381 0.567 0.554 96 134 0.716 168 384 552 214 100 40 97 192 627 0.349 0.053 0.022 0.119 0.056 0.054 0.018 9.358 3.194 8.239
Marc Gasol C 34 TOT 24119025 79 72 2436 390 870 0.448 99 273 0.363 291 597 0.487 0.505 192 253 0.759 80 547 627 349 84 86 155 217 1071 0.440 0.079 0.035 0.143 0.034 0.064 0.041 13.557 4.418 7.937
Marcin Gortat C 34 LAC 13565218 47 43 751 99 186 0.532 0 0 0.000 99 186 0.532 0.532 35 48 0.729 67 194 261 65 6 24 50 92 233 0.310 0.047 0.032 0.087 0.008 0.067 0.000 4.957 1.383 5.553
Mason Plumlee C 28 DEN 12917808 82 17 1731 262 442 0.593 2 10 0.200 260 432 0.602 0.595 111 198 0.561 165 359 524 243 66 76 126 252 637 0.368 0.064 0.044 0.140 0.038 0.073 0.001 7.768 2.963 6.390
Meyers Leonard C 26 POR 10595506 61 2 878 132 242 0.545 50 111 0.450 82 131 0.626 0.649 43 51 0.843 49 184 233 75 13 9 43 105 357 0.407 0.049 0.010 0.085 0.015 0.049 0.057 5.852 1.230 3.820
Mitchell Robinson C 20 NYK 1485440 66 19 1360 202 291 0.694 0 0 0.000 202 291 0.694 0.694 81 135 0.600 177 246 423 37 52 161 35 217 485 0.357 0.060 0.118 0.027 0.038 0.026 0.000 7.348 0.561 6.409
Mo Bamba C 20 ORL 4871280 47 1 766 117 243 0.481 21 70 0.300 96 173 0.555 0.525 37 63 0.587 64 169 233 39 13 64 43 102 292 0.381 0.048 0.084 0.051 0.017 0.056 0.027 6.213 0.830 4.957
Montrezl Harrell C 25 LAC 6000000 82 5 2158 546 888 0.615 3 17 0.176 543 871 0.623 0.617 266 414 0.643 184 351 535 162 71 110 132 255 1361 0.631 0.123 0.051 0.075 0.033 0.061 0.001 16.598 1.976 6.524
Moritz Wagner C 21 LAL 1764240 43 5 446 71 171 0.415 22 77 0.286 49 94 0.521 0.480 43 53 0.811 17 68 85 24 11 13 39 57 207 0.464 0.096 0.029 0.054 0.025 0.087 0.049 4.814 0.558 1.977
Myles Turner C 22 IND 3294994 74 74 2119 380 780 0.487 76 196 0.388 304 584 0.521 0.536 148 201 0.736 101 430 531 115 60 199 100 195 984 0.464 0.070 0.094 0.054 0.028 0.047 0.036 13.297 1.554 7.176
Nerlens Noel C 24 OKC 1757429 77 2 1055 162 276 0.587 0 0 0.000 162 276 0.587 0.587 54 79 0.684 127 198 325 45 66 96 48 166 378 0.358 0.051 0.091 0.043 0.063 0.045 0.000 4.909 0.584 4.221
Pau Gasol C 38 TOT 17133285 30 6 360 42 94 0.447 6 13 0.462 36 81 0.444 0.479 28 40 0.700 22 115 137 52 5 15 16 29 118 0.328 0.078 0.042 0.144 0.014 0.044 0.017 3.933 1.733 4.567
Richaun Holmes C 25 PHO 1600520 70 4 1184 222 365 0.608 0 0 0.000 222 365 0.608 0.608 128 175 0.731 115 216 331 60 42 79 52 194 572 0.483 0.108 0.067 0.051 0.035 0.044 0.000 8.171 0.857 4.729
Robert Williams C 21 BOS 1656600 32 2 283 36 51 0.706 0 0 0.000 36 51 0.706 0.706 9 15 0.600 27 54 81 7 9 40 10 36 81 0.286 0.032 0.141 0.025 0.032 0.035 0.000 2.531 0.219 2.531
Robin Lopez C 30 CHI 14357750 74 36 1606 304 535 0.568 7 31 0.226 297 504 0.589 0.575 89 123 0.724 140 146 286 89 11 78 96 124 704 0.438 0.055 0.049 0.055 0.007 0.060 0.004 9.514 1.203 3.865
Rudy Gobert C 26 UTA 23491573 81 80 2577 476 712 0.669 0 0 0.000 476 712 0.669 0.669 332 522 0.636 309 732 1041 161 66 187 130 231 1284 0.498 0.129 0.073 0.062 0.026 0.050 0.000 15.852 1.988 12.852
Salah Mejri C 32 DAL 2098196 36 4 399 55 112 0.491 11 34 0.324 44 78 0.564 0.540 20 32 0.625 36 95 131 35 10 26 21 55 141 0.353 0.050 0.065 0.088 0.025 0.053 0.028 3.917 0.972 3.639
Serge Ibaka C 29 TOR 21666667 74 51 2010 464 877 0.529 49 169 0.290 415 708 0.586 0.557 135 177 0.763 156 445 601 99 29 103 114 211 1112 0.553 0.067 0.051 0.049 0.014 0.057 0.024 15.027 1.338 8.122
Steven Adams C 25 OKC 24157304 80 80 2669 481 809 0.595 0 2 0.000 481 807 0.596 0.595 146 292 0.500 391 369 760 124 117 76 135 204 1108 0.415 0.055 0.028 0.046 0.044 0.051 0.000 13.850 1.550 9.500
Thomas Bryant C 21 WAS 1378242 72 53 1496 309 502 0.616 33 99 0.333 276 403 0.685 0.648 107 137 0.781 113 341 454 92 25 67 60 126 758 0.507 0.072 0.045 0.061 0.017 0.040 0.022 10.528 1.278 6.306
Tristan Thompson C 27 CLE 17469565 43 40 1198 201 380 0.529 0 0 0.000 201 380 0.529 0.529 68 106 0.642 173 265 438 86 28 16 59 89 470 0.392 0.057 0.013 0.072 0.023 0.049 0.000 10.930 2.000 10.186
Tyson Chandler C 36 TOT 13585000 55 6 875 61 99 0.616 0 1 0.000 61 98 0.622 0.616 51 87 0.586 92 215 307 37 21 23 42 110 173 0.198 0.058 0.026 0.042 0.024 0.048 0.000 3.145 0.673 5.582
Wendell Carter C 19 CHI 4446840 44 44 1110 180 371 0.485 6 32 0.188 174 339 0.513 0.493 89 112 0.795 87 220 307 78 26 58 65 152 455 0.410 0.080 0.052 0.070 0.023 0.059 0.005 10.341 1.773 6.977
Willie Cauley-Stein C 25 SAC 4696874 81 81 2213 412 741 0.556 1 2 0.500 411 739 0.556 0.557 140 254 0.551 181 497 678 194 96 51 84 227 965 0.436 0.063 0.023 0.088 0.043 0.038 0.000 11.914 2.395 8.370
Zach Collins C 21 POR 3628920 77 0 1356 189 400 0.473 40 121 0.331 149 279 0.534 0.523 94 126 0.746 109 215 324 71 25 66 77 174 512 0.378 0.069 0.049 0.052 0.018 0.057 0.029 6.649 0.922 4.208
Zaza Pachulia C 34 DET 2393887 68 3 878 85 193 0.440 0 4 0.000 85 189 0.450 0.440 97 124 0.782 99 166 265 91 31 17 57 151 267 0.304 0.110 0.019 0.104 0.035 0.065 0.000 3.926 1.338 3.897
Thon Maker C-PF 21 TOT 2799720 64 5 972 109 268 0.407 49 153 0.320 60 115 0.522 0.498 56 84 0.667 41 161 202 45 21 51 33 105 323 0.332 0.058 0.052 0.046 0.022 0.034 0.050 5.047 0.703 3.156
Aaron Gordon PF 23 ORL 21590909 78 78 2633 470 1046 0.449 121 347 0.349 349 699 0.499 0.507 185 253 0.731 129 445 574 289 57 56 162 172 1246 0.473 0.070 0.021 0.110 0.022 0.062 0.046 15.974 3.705 7.359
Al-Farouq Aminu PF 28 POR 6957105 81 81 2292 257 593 0.433 96 280 0.343 161 313 0.514 0.514 150 173 0.867 112 498 610 104 68 33 72 143 760 0.332 0.065 0.014 0.045 0.030 0.031 0.042 9.383 1.284 7.531
Alex Poythress PF 25 ATL 77250 21 1 305 40 81 0.494 9 23 0.391 31 58 0.534 0.549 18 29 0.621 29 47 76 17 4 10 13 47 107 0.351 0.059 0.033 0.056 0.013 0.043 0.030 5.095 0.810 3.619
Anthony Tolliver PF 33 MIN 5750000 65 0 1079 99 259 0.382 81 215 0.377 18 44 0.409 0.539 47 60 0.783 15 162 177 46 17 21 36 91 326 0.302 0.044 0.019 0.043 0.016 0.033 0.075 5.015 0.708 2.723
Blake Griffin PF 29 DET 31873932 75 75 2622 619 1341 0.462 189 522 0.362 430 819 0.525 0.532 414 550 0.753 100 465 565 402 52 28 253 199 1841 0.702 0.158 0.011 0.153 0.020 0.096 0.072 24.547 5.360 7.533
Bobby Portis PF 23 TOT 2494346 50 28 1299 279 628 0.444 75 191 0.393 204 437 0.467 0.504 77 97 0.794 109 294 403 72 35 20 74 145 710 0.547 0.059 0.015 0.055 0.027 0.057 0.058 14.200 1.440 8.060
Caleb Swanigan PF 21 TOT 1740000 21 0 178 18 53 0.340 1 7 0.143 17 46 0.370 0.349 6 9 0.667 17 47 64 11 6 1 18 28 43 0.242 0.034 0.006 0.062 0.034 0.101 0.006 2.048 0.524 3.048
Cheick Diallo PF 22 NOP 1544951 64 1 896 168 271 0.620 1 4 0.250 167 267 0.625 0.622 50 67 0.746 75 257 332 33 29 33 49 113 387 0.432 0.056 0.037 0.037 0.032 0.055 0.001 6.047 0.516 5.188
Chimezie Metu PF 21 SAS 838464 29 0 145 19 58 0.328 0 2 0.000 19 56 0.339 0.328 13 17 0.765 9 27 36 13 6 2 15 14 51 0.352 0.090 0.014 0.090 0.041 0.103 0.000 1.759 0.448 1.241
Chris Boucher PF 26 TOR 457418 28 0 163 34 76 0.447 12 37 0.324 22 39 0.564 0.526 13 15 0.867 16 40 56 2 6 24 7 31 93 0.571 0.080 0.147 0.012 0.037 0.043 0.074 3.321 0.071 2.000
Christian Wood PF 23 TOT 1512601 21 2 251 61 117 0.521 9 26 0.346 52 91 0.571 0.560 41 56 0.732 17 66 83 8 7 10 17 17 172 0.685 0.163 0.040 0.032 0.028 0.068 0.036 8.190 0.381 3.952
Dante Cunningham PF 31 SAS 2487000 64 21 928 75 158 0.475 30 65 0.462 45 93 0.484 0.570 14 18 0.778 48 140 188 50 27 13 22 71 194 0.209 0.015 0.014 0.054 0.029 0.024 0.032 3.031 0.781 2.938
DeMarre Carroll PF 32 BRK 15400000 67 8 1703 227 575 0.395 106 310 0.342 121 265 0.457 0.487 184 242 0.760 68 281 349 85 31 10 73 114 744 0.437 0.108 0.006 0.050 0.018 0.043 0.062 11.104 1.269 5.209
Dirk Nowitzki PF 40 DAL 5000000 51 20 795 135 376 0.359 64 205 0.312 71 171 0.415 0.444 39 50 0.780 5 153 158 35 9 18 18 76 373 0.469 0.049 0.023 0.044 0.011 0.023 0.081 7.314 0.686 3.098
Dragan Bender PF 21 PHO 4661280 46 27 826 88 197 0.447 22 101 0.218 66 96 0.688 0.503 32 54 0.593 34 149 183 56 18 22 37 90 230 0.278 0.039 0.027 0.068 0.022 0.045 0.027 5.000 1.217 3.978
Draymond Green PF 28 GSW 17469565 66 66 2065 188 422 0.445 47 165 0.285 141 257 0.549 0.501 63 91 0.692 60 421 481 454 95 70 169 197 486 0.235 0.031 0.034 0.220 0.046 0.082 0.023 7.364 6.879 7.288
Drew Eubanks PF 21 SAS 77250 23 0 113 15 26 0.577 0 0 0.000 15 26 0.577 0.577 11 13 0.846 6 28 34 7 2 5 8 11 41 0.363 0.097 0.044 0.062 0.018 0.071 0.000 1.783 0.304 1.478
Gary Clark PF 24 HOU 674122 51 2 641 50 151 0.331 41 138 0.297 9 13 0.692 0.467 7 7 1.000 24 92 116 18 20 26 7 47 148 0.231 0.011 0.041 0.028 0.031 0.011 0.064 2.902 0.353 2.275
Georges Niang PF 25 UTA 1512601 59 0 516 86 181 0.475 43 105 0.410 43 76 0.566 0.594 20 24 0.833 11 76 87 35 10 6 23 57 235 0.455 0.039 0.012 0.068 0.019 0.045 0.083 3.983 0.593 1.475
Giannis Antetokounmpo PF 24 MIL 24157304 72 72 2358 721 1247 0.578 52 203 0.256 669 1044 0.641 0.599 500 686 0.729 159 739 898 424 92 110 268 232 1994 0.846 0.212 0.047 0.180 0.039 0.114 0.022 27.694 5.889 12.472
Gordon Hayward PF 28 BOS 31214295 72 18 1863 296 635 0.466 77 231 0.333 219 404 0.542 0.527 156 187 0.834 51 271 322 244 62 23 105 104 825 0.443 0.084 0.012 0.131 0.033 0.056 0.041 11.458 3.389 4.472
Guerschon Yabusele PF 23 BOS 2667600 41 1 251 35 77 0.455 9 28 0.321 26 49 0.531 0.513 15 22 0.682 23 30 53 15 8 7 15 32 94 0.375 0.060 0.028 0.060 0.032 0.060 0.036 2.293 0.366 1.293
Harry Giles PF 20 SAC 2207040 58 0 820 175 348 0.503 0 6 0.000 175 342 0.512 0.503 58 91 0.637 66 156 222 85 31 22 73 150 408 0.498 0.071 0.027 0.104 0.038 0.089 0.000 7.034 1.466 3.828
Isaiah Hartenstein PF 20 HOU 838464 28 0 221 20 41 0.488 2 6 0.333 18 35 0.514 0.512 11 14 0.786 21 26 47 15 7 12 13 56 53 0.240 0.050 0.054 0.068 0.032 0.059 0.009 1.893 0.536 1.679
Ivan Rabb PF 21 MEM 1378242 49 13 721 116 212 0.547 3 15 0.200 113 197 0.574 0.554 49 69 0.710 70 136 206 54 17 14 35 90 284 0.394 0.068 0.019 0.075 0.024 0.049 0.004 5.796 1.102 4.204
Jabari Parker PF 23 TOT 20000000 64 17 1724 369 749 0.493 61 195 0.313 308 554 0.556 0.533 131 184 0.712 79 342 421 152 46 30 151 145 930 0.539 0.076 0.017 0.088 0.027 0.088 0.035 14.531 2.375 6.578
James Johnson PF 31 MIA 14420700 55 33 1164 164 379 0.433 50 149 0.336 114 230 0.496 0.499 50 70 0.714 22 154 176 135 35 27 74 114 428 0.368 0.043 0.023 0.116 0.030 0.064 0.043 7.782 2.455 3.200
JaMychal Green PF 28 TOT 8066667 65 6 1371 230 476 0.483 71 176 0.403 159 300 0.530 0.558 80 101 0.792 104 305 409 50 45 34 87 193 611 0.446 0.058 0.025 0.036 0.033 0.063 0.052 9.400 0.769 6.292
Jared Dudley PF 33 BRK 9530000 59 25 1220 101 239 0.423 53 151 0.351 48 88 0.545 0.533 32 46 0.696 34 121 155 83 36 16 43 131 287 0.235 0.026 0.013 0.068 0.030 0.035 0.043 4.864 1.407 2.627
Jarell Martin PF 24 ORL 2416221 42 1 328 43 104 0.413 20 57 0.351 23 47 0.489 0.510 9 11 0.818 11 62 73 18 3 8 11 51 115 0.351 0.027 0.024 0.055 0.009 0.034 0.061 2.738 0.429 1.738
Jaren Jackson PF 19 MEM 5922720 58 56 1515 298 589 0.506 51 142 0.359 247 447 0.553 0.549 151 197 0.766 73 199 272 64 52 82 98 220 798 0.527 0.100 0.054 0.042 0.034 0.065 0.034 13.759 1.103 4.690
Jeff Green PF 32 WAS 2393887 77 44 2097 326 687 0.475 111 320 0.347 215 367 0.586 0.555 183 206 0.888 57 252 309 137 43 39 101 160 946 0.451 0.087 0.019 0.065 0.021 0.048 0.053 12.286 1.779 4.013
Jerami Grant PF 24 OKC 8333333 80 77 2612 409 823 0.497 115 293 0.392 294 530 0.555 0.567 157 221 0.710 96 321 417 79 61 100 67 214 1090 0.417 0.060 0.038 0.030 0.023 0.026 0.044 13.625 0.988 5.213
Joe Ingles PF 31 UTA 12545455 82 82 2568 359 802 0.448 189 483 0.391 170 319 0.533 0.565 87 123 0.707 35 295 330 469 98 20 193 180 994 0.387 0.034 0.008 0.183 0.038 0.075 0.074 12.122 5.720 4.024
John Collins PF 21 ATL 2299080 61 59 1829 465 831 0.560 55 158 0.348 410 673 0.609 0.593 203 266 0.763 219 376 595 121 22 39 120 199 1188 0.650 0.111 0.021 0.066 0.012 0.066 0.030 19.475 1.984 9.754
Johnathan Motley PF 23 LAC 77250 22 0 156 39 73 0.534 0 3 0.000 39 70 0.557 0.534 24 40 0.600 18 33 51 11 5 3 16 27 102 0.654 0.154 0.019 0.071 0.032 0.103 0.000 4.636 0.500 2.318
Jon Leuer PF 29 DET 10002681 41 1 402 66 113 0.584 1 11 0.091 65 102 0.637 0.588 23 31 0.742 27 70 97 14 12 4 23 60 156 0.388 0.057 0.010 0.035 0.030 0.057 0.002 3.805 0.341 2.366
Jonah Bolden PF 23 PHI 1690000 44 10 639 80 162 0.494 34 96 0.354 46 66 0.697 0.599 13 27 0.481 47 118 165 40 17 39 36 99 207 0.324 0.020 0.061 0.063 0.027 0.056 0.053 4.705 0.909 3.750
Jonas Jerebko PF 31 GSW 2165481 73 6 1218 163 355 0.459 69 188 0.367 94 167 0.563 0.556 64 80 0.800 72 216 288 96 27 18 43 137 459 0.377 0.053 0.015 0.079 0.022 0.035 0.057 6.288 1.315 3.945
Jonathan Isaac PF 21 ORL 4969080 75 64 1996 262 611 0.429 86 266 0.323 176 345 0.510 0.499 110 135 0.815 99 312 411 80 59 98 75 143 720 0.361 0.055 0.049 0.040 0.030 0.038 0.043 9.600 1.067 5.480
Julius Randle PF 24 NOP 8641000 73 49 2232 571 1089 0.524 67 195 0.344 504 894 0.564 0.555 356 487 0.731 162 472 634 229 52 45 208 246 1565 0.701 0.159 0.020 0.103 0.023 0.093 0.030 21.438 3.137 8.685
Kelly Olynyk PF 27 MIA 13537527 79 36 1812 261 564 0.463 113 319 0.354 148 245 0.604 0.563 152 185 0.822 72 303 375 140 53 37 114 183 787 0.434 0.084 0.020 0.077 0.029 0.063 0.062 9.962 1.772 4.747
Kevin Knox PF 19 NYK 3744840 75 57 2158 338 914 0.370 125 364 0.343 213 550 0.387 0.438 162 226 0.717 61 274 335 82 43 24 114 175 963 0.446 0.075 0.011 0.038 0.020 0.053 0.058 12.840 1.093 4.467
Kevin Love PF 30 CLE 24119025 22 21 598 109 283 0.385 53 147 0.361 56 136 0.412 0.479 103 114 0.904 33 206 239 48 6 5 42 54 374 0.625 0.172 0.008 0.080 0.010 0.070 0.089 17.000 2.182 10.864
Kyle Kuzma PF 23 LAL 1689840 70 68 2314 496 1087 0.456 128 422 0.303 368 665 0.553 0.515 188 250 0.752 60 322 382 178 41 26 133 170 1308 0.565 0.081 0.011 0.077 0.018 0.057 0.055 18.686 2.543 5.457
Lance Thomas PF 30 NYK 7119650 46 17 783 78 197 0.396 22 79 0.278 56 118 0.475 0.452 27 36 0.750 21 96 117 27 17 7 24 83 205 0.262 0.034 0.009 0.034 0.022 0.031 0.028 4.457 0.587 2.543
Lauri Markkanen PF 21 CHI 4536120 52 51 1682 342 795 0.430 120 332 0.361 222 463 0.479 0.506 170 195 0.872 74 396 470 75 37 33 85 122 974 0.579 0.101 0.020 0.045 0.022 0.051 0.071 18.731 1.442 9.038
Luke Kornet PF 23 NYK 1619260 46 18 784 107 283 0.378 70 193 0.363 37 90 0.411 0.502 38 46 0.826 28 107 135 54 27 42 25 41 322 0.411 0.048 0.054 0.069 0.034 0.032 0.089 7.000 1.174 2.935
Marcus Morris PF 29 BOS 5375000 75 53 2091 377 844 0.447 146 389 0.375 231 455 0.508 0.533 146 173 0.844 76 382 458 109 43 25 92 181 1046 0.500 0.070 0.012 0.052 0.021 0.044 0.070 13.947 1.453 6.107
Markieff Morris PF 29 TOT 9173294 58 16 1270 204 484 0.421 68 203 0.335 136 281 0.484 0.492 71 92 0.772 61 204 265 79 36 22 54 175 547 0.431 0.056 0.017 0.062 0.028 0.043 0.054 9.431 1.362 4.569
Marquese Chriss PF 21 TOT 3206160 43 2 499 67 180 0.372 16 72 0.222 51 108 0.472 0.417 32 45 0.711 40 102 142 22 17 11 36 81 182 0.365 0.064 0.022 0.044 0.034 0.072 0.032 4.233 0.512 3.302
Marvin Bagley PF 19 SAC 7314960 62 4 1567 356 706 0.504 30 96 0.313 326 610 0.534 0.525 181 262 0.691 162 309 471 62 33 59 98 120 923 0.589 0.116 0.038 0.040 0.021 0.063 0.019 14.887 1.000 7.597
Marvin Williams PF 32 CHO 14087500 75 75 2133 275 652 0.422 140 382 0.366 135 270 0.500 0.529 66 86 0.767 76 331 407 92 71 61 47 156 756 0.354 0.031 0.029 0.043 0.033 0.022 0.066 10.080 1.227 5.427
Maxi Kleber PF 27 DAL 1378242 71 18 1502 175 386 0.453 77 218 0.353 98 168 0.583 0.553 58 74 0.784 90 239 329 70 36 78 54 143 485 0.323 0.039 0.052 0.047 0.024 0.036 0.051 6.831 0.986 4.634
Michael Beasley PF 30 LAL 3500000 26 2 277 75 153 0.490 3 17 0.176 72 136 0.529 0.500 28 39 0.718 13 47 60 25 9 10 27 42 181 0.653 0.101 0.036 0.090 0.032 0.097 0.011 6.962 0.962 2.308
Michael Kidd-Gilchrist PF 25 CHO 13000000 64 3 1179 158 332 0.476 16 47 0.340 142 285 0.498 0.500 95 123 0.772 88 158 246 61 32 39 43 156 427 0.362 0.081 0.033 0.052 0.027 0.036 0.014 6.672 0.953 3.844
Mike Muscala PF 27 TOT 5000000 64 10 1306 145 361 0.402 89 256 0.348 56 105 0.533 0.525 70 85 0.824 57 187 244 76 22 38 48 130 449 0.344 0.054 0.029 0.058 0.017 0.037 0.068 7.016 1.188 3.812
Mike Scott PF 30 TOT 4320500 79 3 1395 168 420 0.400 101 252 0.401 67 168 0.399 0.520 22 33 0.667 43 233 276 66 26 13 44 156 459 0.329 0.016 0.009 0.047 0.019 0.032 0.072 5.810 0.835 3.494
Nemanja Bjelica PF 30 SAC 6500000 77 70 1788 284 593 0.479 103 257 0.401 181 336 0.539 0.566 70 92 0.761 125 319 444 147 54 56 82 197 741 0.414 0.039 0.031 0.082 0.030 0.046 0.058 9.623 1.909 5.766
Noah Vonleh PF 23 NYK 1621415 68 57 1722 207 440 0.470 46 137 0.336 161 303 0.531 0.523 111 156 0.712 113 415 528 129 46 51 88 174 571 0.332 0.064 0.030 0.075 0.027 0.051 0.027 8.397 1.897 7.765
Omari Spellman PF 21 ATL 1622520 46 11 805 98 244 0.402 44 128 0.344 54 116 0.466 0.492 32 45 0.711 72 122 194 47 26 25 31 67 272 0.338 0.040 0.031 0.058 0.032 0.039 0.055 5.913 1.022 4.217
Pascal Siakam PF 24 TOR 1544951 80 79 2548 519 945 0.549 79 214 0.369 440 731 0.602 0.591 237 302 0.785 124 425 549 248 73 52 154 241 1354 0.531 0.093 0.020 0.097 0.029 0.060 0.031 16.925 3.100 6.862
Patrick Patterson PF 29 OKC 5451600 63 5 861 82 219 0.374 46 137 0.336 36 82 0.439 0.479 19 30 0.633 42 105 147 31 16 13 22 46 229 0.266 0.022 0.015 0.036 0.019 0.026 0.053 3.635 0.492 2.333
Paul Millsap PF 33 DEN 29230769 70 65 1895 322 665 0.484 58 159 0.365 264 506 0.522 0.528 181 249 0.727 153 352 505 141 83 54 95 183 883 0.466 0.096 0.028 0.074 0.044 0.050 0.031 12.614 2.014 7.214
Rudy Gay PF 32 SAS 10087200 69 51 1842 376 746 0.504 74 184 0.402 302 562 0.537 0.554 120 147 0.816 63 407 470 182 54 34 114 159 946 0.514 0.065 0.018 0.099 0.029 0.062 0.040 13.710 2.638 6.812
Ryan Anderson PF 30 TOT 20421546 25 8 322 21 69 0.304 9 40 0.225 12 29 0.414 0.370 12 16 0.750 18 36 54 19 4 1 14 25 63 0.196 0.037 0.003 0.059 0.012 0.043 0.028 2.520 0.760 2.160
Sam Dekker PF 24 TOT 2760094 47 5 788 120 256 0.469 19 62 0.306 101 194 0.521 0.506 28 46 0.609 53 95 148 46 38 7 24 47 287 0.364 0.036 0.009 0.058 0.048 0.030 0.024 6.106 0.979 3.149
Semi Ojeleye PF 24 BOS 1378242 56 3 594 67 158 0.424 28 89 0.315 39 69 0.565 0.513 24 39 0.615 24 62 86 23 10 4 19 43 186 0.313 0.040 0.007 0.039 0.017 0.032 0.047 3.321 0.411 1.536
Taj Gibson PF 33 MIN 14000000 70 57 1686 304 537 0.566 11 34 0.324 293 503 0.583 0.576 134 177 0.757 172 286 458 84 53 39 73 186 753 0.447 0.079 0.023 0.050 0.031 0.043 0.007 10.757 1.200 6.543
Thaddeus Young PF 30 IND 13764045 81 81 2489 443 841 0.527 51 146 0.349 392 695 0.564 0.557 87 135 0.644 192 331 523 204 123 36 123 194 1024 0.411 0.035 0.014 0.082 0.049 0.049 0.020 12.642 2.519 6.457
Tobias Harris PF 26 TOT 14800000 82 82 2847 611 1254 0.487 156 393 0.397 455 861 0.528 0.549 266 307 0.866 69 576 645 229 51 37 151 184 1644 0.577 0.093 0.013 0.080 0.018 0.053 0.055 20.049 2.793 7.866
Trey Lyles PF 23 DEN 3364249 64 2 1120 207 495 0.418 51 200 0.255 156 295 0.529 0.470 81 116 0.698 44 202 246 87 30 23 68 93 546 0.488 0.072 0.021 0.078 0.027 0.061 0.046 8.531 1.359 3.844
Vince Carter PF 42 ATL 2393887 76 9 1330 196 468 0.419 123 316 0.389 73 152 0.480 0.550 47 66 0.712 31 163 194 87 44 27 48 141 562 0.423 0.035 0.020 0.065 0.033 0.036 0.092 7.395 1.145 2.553
Jason Smith PF-C 32 TOT 5450000 20 1 190 21 59 0.356 9 26 0.346 12 33 0.364 0.432 14 16 0.875 16 36 52 14 3 7 13 30 65 0.342 0.074 0.037 0.074 0.016 0.068 0.047 3.250 0.700 2.600
Harrison Barnes PF-SF 26 TOT 24107258 77 77 2533 431 1027 0.420 174 441 0.395 257 586 0.439 0.504 229 278 0.824 57 304 361 115 50 13 98 122 1265 0.499 0.090 0.005 0.045 0.020 0.039 0.069 16.429 1.494 4.688
Wilson Chandler PF-SF 31 TOT 12800562 51 33 1177 114 273 0.418 59 158 0.373 55 115 0.478 0.526 18 25 0.720 48 167 215 82 25 21 46 123 305 0.259 0.015 0.018 0.070 0.021 0.039 0.050 5.980 1.608 4.216
Aaron Holiday PG 22 IND 1914480 50 0 646 105 262 0.401 43 127 0.339 62 135 0.459 0.483 41 50 0.820 5 62 67 87 21 13 40 71 294 0.455 0.063 0.020 0.135 0.033 0.062 0.067 5.880 1.740 1.340
Alex Caruso PG 24 LAL 77250 25 4 531 77 173 0.445 24 50 0.480 53 123 0.431 0.514 51 64 0.797 20 47 67 77 24 9 42 54 229 0.431 0.096 0.017 0.145 0.045 0.079 0.045 9.160 3.080 2.680
Ben Simmons PG 22 PHI 6434520 79 79 2700 540 960 0.563 0 6 0.000 540 954 0.566 0.563 257 428 0.600 172 525 697 610 112 61 274 209 1337 0.495 0.095 0.023 0.226 0.041 0.101 0.000 16.924 7.722 8.823
Brad Wanamaker PG 29 BOS 838464 36 0 343 50 105 0.476 16 39 0.410 34 66 0.515 0.552 24 28 0.857 3 38 41 56 12 2 19 34 140 0.408 0.070 0.006 0.163 0.035 0.055 0.047 3.889 1.556 1.139
Brandon Knight PG 27 TOT 14631250 39 26 736 99 260 0.381 41 129 0.318 58 131 0.443 0.460 27 34 0.794 10 49 59 71 21 2 30 62 266 0.361 0.037 0.003 0.096 0.029 0.041 0.056 6.821 1.821 1.513
Cameron Payne PG 24 TOT 3440356 40 13 712 96 223 0.430 25 84 0.298 71 139 0.511 0.487 33 41 0.805 13 59 72 106 28 9 45 64 250 0.351 0.046 0.013 0.149 0.039 0.063 0.035 6.250 2.650 1.800
Chasson Randle PG 25 WAS 975824 49 2 743 91 217 0.419 46 115 0.400 45 102 0.441 0.525 43 62 0.694 10 46 56 97 25 3 43 91 271 0.365 0.058 0.004 0.131 0.034 0.058 0.062 5.531 1.980 1.143
Chris Paul PG 33 HOU 35654150 58 58 1857 302 720 0.419 127 355 0.358 175 365 0.479 0.508 175 203 0.862 36 229 265 473 114 18 152 146 906 0.488 0.094 0.010 0.255 0.061 0.082 0.068 15.621 8.155 4.569
Collin Sexton PG 20 CLE 4073760 82 72 2605 519 1206 0.430 119 296 0.402 400 910 0.440 0.480 214 255 0.839 57 179 236 243 44 6 185 186 1371 0.526 0.082 0.002 0.093 0.017 0.071 0.046 16.720 2.963 2.878
Cory Joseph PG 27 IND 7945000 82 9 2063 226 548 0.412 55 171 0.322 171 377 0.454 0.463 30 43 0.698 39 240 279 321 94 22 80 131 537 0.260 0.015 0.011 0.156 0.046 0.039 0.027 6.549 3.915 3.402
D’Angelo Russell PG 22 BRK 7019698 81 81 2448 659 1517 0.434 234 635 0.369 425 882 0.482 0.512 160 205 0.780 53 262 315 563 100 20 253 141 1712 0.699 0.065 0.008 0.230 0.041 0.103 0.096 21.136 6.951 3.889
Damian Lillard PG 28 POR 27977689 80 80 2838 681 1533 0.444 237 643 0.369 444 890 0.499 0.522 468 513 0.912 68 303 371 551 88 34 212 148 2067 0.728 0.165 0.012 0.194 0.031 0.075 0.084 25.837 6.888 4.638
Dante Exum PG 23 UTA 10600000 42 1 664 101 241 0.419 18 62 0.290 83 179 0.464 0.456 68 86 0.791 16 52 68 110 14 5 52 69 288 0.434 0.102 0.008 0.166 0.021 0.078 0.027 6.857 2.619 1.619
Darren Collison PG 31 IND 10000000 76 76 2143 308 659 0.467 79 194 0.407 229 465 0.492 0.527 158 190 0.832 36 196 232 459 110 9 125 138 853 0.398 0.074 0.004 0.214 0.051 0.058 0.037 11.224 6.039 3.053
De’Aaron Fox PG 21 SAC 5470920 81 81 2546 505 1102 0.458 86 232 0.371 419 870 0.482 0.497 303 417 0.727 43 261 304 590 133 45 227 204 1399 0.549 0.119 0.018 0.232 0.052 0.089 0.034 17.272 7.284 3.753
De’Anthony Melton PG 20 PHO 949000 50 31 984 100 256 0.391 29 95 0.305 71 161 0.441 0.447 21 28 0.750 25 109 134 159 68 23 75 113 250 0.254 0.021 0.023 0.162 0.069 0.076 0.029 5.000 3.180 2.680
Delon Wright PG 26 TOT 2536898 75 13 1699 242 558 0.434 50 168 0.298 192 390 0.492 0.478 119 150 0.793 68 198 266 248 88 30 77 103 653 0.384 0.070 0.018 0.146 0.052 0.045 0.029 8.707 3.307 3.547
Dennis Smith PG 21 TOT 3819960 53 50 1508 278 650 0.428 67 208 0.322 211 442 0.477 0.479 99 156 0.635 32 123 155 252 67 20 154 129 722 0.479 0.066 0.013 0.167 0.044 0.102 0.044 13.623 4.755 2.925
Derrick Rose PG 30 MIN 2176260 51 13 1392 363 753 0.482 54 146 0.370 309 607 0.509 0.518 137 160 0.856 33 107 140 220 31 12 82 57 917 0.659 0.098 0.009 0.158 0.022 0.059 0.039 17.980 4.314 2.745
Derrick White PG 24 SAS 1667160 67 55 1728 260 543 0.479 48 142 0.338 212 401 0.529 0.523 95 123 0.772 35 212 247 263 67 47 97 145 663 0.384 0.055 0.027 0.152 0.039 0.056 0.028 9.896 3.925 3.687
Devin Harris PG 35 DAL 2393887 68 2 1071 132 347 0.380 62 200 0.310 70 147 0.476 0.470 102 134 0.761 12 100 112 122 35 16 56 133 428 0.400 0.095 0.015 0.114 0.033 0.052 0.058 6.294 1.794 1.647
Edmond Sumner PG 23 IND 449794 23 2 210 22 64 0.344 7 27 0.259 15 37 0.405 0.398 15 24 0.625 9 15 24 10 12 5 10 26 66 0.314 0.071 0.024 0.048 0.057 0.048 0.033 2.870 0.435 1.043
Elfrid Payton PG 24 NOP 3000000 42 42 1250 179 412 0.434 33 105 0.314 146 307 0.476 0.475 55 74 0.743 49 171 220 320 44 17 112 81 446 0.357 0.044 0.014 0.256 0.035 0.090 0.026 10.619 7.619 5.238
Elie Okobo PG 21 PHO 1238464 53 16 958 114 290 0.393 39 132 0.295 75 158 0.475 0.460 37 47 0.787 12 86 98 127 32 7 69 109 304 0.317 0.039 0.007 0.133 0.033 0.072 0.041 5.736 2.396 1.849
Emmanuel Mudiay PG 22 NYK 4294479 59 42 1607 330 740 0.446 69 210 0.329 261 530 0.492 0.493 144 186 0.774 33 163 196 228 43 19 140 103 873 0.543 0.090 0.012 0.142 0.027 0.087 0.043 14.797 3.864 3.322
Eric Bledsoe PG 29 MIL 15000000 78 78 2272 470 971 0.484 124 377 0.329 346 594 0.582 0.548 177 236 0.750 82 280 362 430 116 29 165 156 1241 0.546 0.078 0.013 0.189 0.051 0.073 0.055 15.910 5.513 4.641
Evan Turner PG 30 POR 17868853 73 2 1605 204 443 0.460 11 52 0.212 193 391 0.494 0.473 75 106 0.708 37 291 328 283 33 18 114 110 494 0.308 0.047 0.011 0.176 0.021 0.071 0.007 6.767 3.877 4.493
Frank Jackson PG 20 NOP 1378242 61 16 1169 194 447 0.434 53 169 0.314 141 278 0.507 0.493 54 73 0.740 25 109 134 69 25 2 48 92 495 0.423 0.046 0.002 0.059 0.021 0.041 0.045 8.115 1.131 2.197
Frank Mason PG 24 SAC 1378242 38 0 435 71 169 0.420 14 64 0.219 57 105 0.543 0.462 39 57 0.684 6 37 43 84 16 4 36 34 195 0.448 0.090 0.009 0.193 0.037 0.083 0.032 5.132 2.211 1.132
Frank Ntilikina PG 20 NYK 4155720 43 16 904 95 282 0.337 33 115 0.287 62 167 0.371 0.395 23 30 0.767 12 75 87 121 30 14 56 104 246 0.272 0.025 0.015 0.134 0.033 0.062 0.037 5.721 2.814 2.023
Fred VanVleet PG 24 TOR 8653847 64 28 1760 246 600 0.410 112 296 0.378 134 304 0.441 0.503 97 115 0.843 21 146 167 307 57 20 82 110 701 0.398 0.055 0.011 0.174 0.032 0.047 0.064 10.953 4.797 2.609
George Hill PG 32 TOT 19000000 60 13 1302 170 376 0.452 48 153 0.314 122 223 0.547 0.516 70 85 0.824 39 109 148 135 52 8 51 102 458 0.352 0.054 0.006 0.104 0.040 0.039 0.037 7.633 2.250 2.467
Isaac Bonga PG 19 LAL 1000000 22 0 120 5 33 0.152 0 8 0.000 5 25 0.200 0.152 9 15 0.600 9 16 25 15 9 4 6 9 19 0.158 0.075 0.033 0.125 0.075 0.050 0.000 0.864 0.682 1.136
Isaiah Briscoe PG 22 ORL 838464 39 0 559 55 138 0.399 11 34 0.324 44 104 0.423 0.438 15 26 0.577 5 69 74 87 11 2 31 66 136 0.243 0.027 0.004 0.156 0.020 0.055 0.020 3.487 2.231 1.897
Isaiah Canaan PG 27 TOT 744671 30 16 629 64 164 0.390 34 96 0.354 30 68 0.441 0.494 19 24 0.792 6 52 58 84 14 2 35 52 181 0.288 0.030 0.003 0.134 0.022 0.056 0.054 6.033 2.800 1.933
Jalen Brunson PG 22 DAL 1230000 73 38 1591 264 565 0.467 63 181 0.348 201 384 0.523 0.523 87 120 0.725 25 144 169 230 37 4 88 127 678 0.426 0.055 0.003 0.145 0.023 0.055 0.040 9.288 3.151 2.315
Jamal Murray PG 21 DEN 3499800 75 74 2447 513 1173 0.437 152 414 0.367 361 759 0.476 0.502 189 223 0.848 65 252 317 363 67 27 158 153 1367 0.559 0.077 0.011 0.148 0.027 0.065 0.062 18.227 4.840 4.227
James Harden PG 29 HOU 30570000 78 78 2867 843 1909 0.442 378 1028 0.368 465 881 0.528 0.541 754 858 0.879 66 452 518 586 158 58 387 244 2818 0.983 0.263 0.020 0.204 0.055 0.135 0.132 36.128 7.513 6.641
Jaylen Adams PG 22 ATL 236854 34 1 428 38 110 0.345 25 74 0.338 13 36 0.361 0.459 7 9 0.778 11 49 60 65 14 5 28 45 108 0.252 0.016 0.012 0.152 0.033 0.065 0.058 3.176 1.912 1.765
Jeff Teague PG 30 MIN 19000000 42 41 1264 176 416 0.423 35 105 0.333 141 311 0.453 0.465 123 153 0.804 16 90 106 343 43 18 97 90 510 0.403 0.097 0.014 0.271 0.034 0.077 0.028 12.143 8.167 2.524
Jeremy Lin PG 30 TOT 12516746 74 4 1436 238 541 0.440 55 187 0.294 183 354 0.517 0.491 176 210 0.838 22 157 179 231 47 13 124 144 707 0.492 0.123 0.009 0.161 0.033 0.086 0.038 9.554 3.122 2.419
Jerian Grant PG 26 ORL 2639313 60 1 939 92 220 0.418 40 110 0.364 52 110 0.473 0.509 26 40 0.650 19 79 98 156 44 6 51 78 250 0.266 0.028 0.006 0.166 0.047 0.054 0.043 4.167 2.600 1.633
Jerryd Bayless PG 30 MIN 8575916 34 6 657 82 230 0.357 29 98 0.296 53 132 0.402 0.420 16 28 0.571 11 51 62 119 18 2 32 56 209 0.318 0.024 0.003 0.181 0.027 0.049 0.044 6.147 3.500 1.824
Jevon Carter PG 23 MEM 838464 39 3 577 56 185 0.303 34 102 0.333 22 83 0.265 0.395 26 32 0.813 14 52 66 69 26 11 33 55 172 0.298 0.045 0.019 0.120 0.045 0.057 0.059 4.410 1.769 1.692
John Wall PG 28 WAS 19169800 32 32 1104 245 552 0.444 51 169 0.302 194 383 0.507 0.490 122 175 0.697 15 101 116 279 49 29 121 71 663 0.601 0.111 0.026 0.253 0.044 0.110 0.046 20.719 8.719 3.625
Kemba Walker PG 28 CHO 12000000 82 82 2863 731 1684 0.434 260 731 0.356 471 953 0.494 0.511 380 450 0.844 52 309 361 484 102 34 211 131 2102 0.734 0.133 0.012 0.169 0.036 0.074 0.091 25.634 5.902 4.402
Kris Dunn PG 24 CHI 4221000 46 44 1389 215 506 0.425 34 96 0.354 181 410 0.441 0.458 55 69 0.797 19 168 187 277 68 21 104 166 519 0.374 0.040 0.015 0.199 0.049 0.075 0.024 11.283 6.022 4.065
Kyle Lowry PG 32 TOR 32700000 65 65 2213 304 739 0.411 157 453 0.347 147 286 0.514 0.518 161 194 0.830 41 271 312 564 91 31 182 166 926 0.418 0.073 0.014 0.255 0.041 0.082 0.071 14.246 8.677 4.800
Kyrie Irving PG 26 BOS 20099189 67 67 2214 604 1241 0.487 174 434 0.401 430 807 0.533 0.557 214 245 0.873 71 264 335 464 103 34 172 167 1596 0.721 0.097 0.015 0.210 0.047 0.078 0.079 23.821 6.925 5.000
Lonzo Ball PG 21 LAL 7461960 47 45 1423 185 456 0.406 75 228 0.329 110 228 0.482 0.488 20 48 0.417 54 197 251 255 69 19 103 114 465 0.327 0.014 0.013 0.179 0.048 0.072 0.053 9.894 5.426 5.340
Lorenzo Brown PG 28 TOR 800000 26 0 212 23 71 0.324 6 28 0.214 17 43 0.395 0.366 3 3 1.000 5 26 31 28 12 5 16 22 55 0.259 0.014 0.024 0.132 0.057 0.075 0.028 2.115 1.077 1.192
Matthew Dellavedova PG 28 TOT 9607500 48 0 812 98 242 0.405 44 130 0.338 54 112 0.482 0.496 42 52 0.808 6 71 77 181 14 2 68 75 282 0.347 0.052 0.002 0.223 0.017 0.084 0.054 5.875 3.771 1.604
Michael Carter-Williams PG 27 TOT 1468082 28 1 372 46 123 0.374 10 38 0.263 36 85 0.424 0.415 32 53 0.604 19 51 70 70 20 15 20 48 134 0.360 0.086 0.040 0.188 0.054 0.054 0.027 4.786 2.500 2.500
Mike Conley PG 31 MEM 30521115 70 70 2342 490 1120 0.438 155 426 0.364 335 694 0.483 0.507 343 406 0.845 40 199 239 449 94 22 130 123 1478 0.631 0.146 0.009 0.192 0.040 0.056 0.066 21.114 6.414 3.414
Monte Morris PG 23 DEN 1349383 82 6 1970 346 702 0.493 94 227 0.414 252 475 0.531 0.560 65 81 0.802 35 159 194 297 73 4 52 102 851 0.432 0.033 0.002 0.151 0.037 0.026 0.048 10.378 3.622 2.366
Patrick Beverley PG 30 LAC 5027028 78 49 2137 194 477 0.407 112 282 0.397 82 195 0.421 0.524 96 123 0.780 76 312 388 300 67 43 85 265 596 0.279 0.045 0.020 0.140 0.031 0.040 0.052 7.641 3.846 4.974
Quinn Cook PG 25 GSW 1544951 74 10 1059 204 439 0.465 81 200 0.405 123 239 0.515 0.557 20 26 0.769 22 135 157 116 20 3 50 92 509 0.481 0.019 0.003 0.110 0.019 0.047 0.076 6.878 1.568 2.122
Rajon Rondo PG 32 LAL 9000000 46 29 1369 175 432 0.405 51 142 0.359 124 290 0.428 0.464 23 36 0.639 34 209 243 367 57 7 127 100 424 0.310 0.017 0.005 0.268 0.042 0.093 0.037 9.217 7.978 5.283
Raul Neto PG 26 UTA 2100000 37 1 474 74 161 0.460 20 60 0.333 54 101 0.535 0.522 28 33 0.848 6 56 62 93 14 4 35 49 196 0.414 0.059 0.008 0.196 0.030 0.074 0.042 5.297 2.514 1.676
Raymond Felton PG 34 OKC 2393887 33 0 379 55 135 0.407 20 61 0.328 35 74 0.473 0.481 12 13 0.923 4 30 34 52 10 6 14 29 142 0.375 0.032 0.016 0.137 0.026 0.037 0.053 4.303 1.576 1.030
Reggie Jackson PG 28 DET 17043478 82 82 2289 441 1047 0.421 174 471 0.369 267 576 0.464 0.504 204 236 0.864 45 171 216 344 55 9 148 208 1260 0.550 0.089 0.004 0.150 0.024 0.065 0.076 15.366 4.195 2.634
Ricky Rubio PG 28 UTA 14800000 68 67 1899 295 730 0.404 79 254 0.311 216 476 0.454 0.458 195 228 0.855 33 210 243 416 91 10 180 180 864 0.455 0.103 0.005 0.219 0.048 0.095 0.042 12.706 6.118 3.574
Russell Westbrook PG 30 OKC 35665000 73 73 2630 630 1473 0.428 119 411 0.290 511 1062 0.481 0.468 296 451 0.656 109 698 807 784 142 33 325 245 1675 0.637 0.113 0.013 0.298 0.054 0.124 0.045 22.945 10.740 11.055
Ryan Arcidiacono PG 24 CHI 1349383 81 32 1961 187 418 0.447 81 217 0.373 106 201 0.527 0.544 89 102 0.873 27 192 219 269 65 4 63 171 544 0.277 0.045 0.002 0.137 0.033 0.032 0.041 6.716 3.321 2.704
Shabazz Napier PG 27 BRK 1942422 56 2 983 169 435 0.389 76 228 0.333 93 207 0.449 0.476 115 138 0.833 18 82 100 143 41 16 66 67 529 0.538 0.117 0.016 0.145 0.042 0.067 0.077 9.446 2.554 1.786
Shai Gilgeous-Alexander PG 20 LAC 3375360 82 73 2174 341 716 0.476 51 139 0.367 290 577 0.503 0.512 156 195 0.800 57 175 232 270 96 45 141 175 889 0.409 0.072 0.021 0.124 0.044 0.065 0.023 10.841 3.293 2.829
Shaquille Harrison PG 25 CHI 1325531 73 11 1430 184 426 0.432 24 89 0.270 160 337 0.475 0.460 82 123 0.667 33 189 222 139 89 30 60 124 474 0.331 0.057 0.021 0.097 0.062 0.042 0.017 6.493 1.904 3.041
Shaun Livingston PG 33 GSW 8307692 64 0 967 109 210 0.519 0 2 0.000 109 208 0.524 0.519 40 51 0.784 42 75 117 114 31 27 38 74 258 0.267 0.041 0.028 0.118 0.032 0.039 0.000 4.031 1.781 1.828
Shelvin Mack PG 28 TOT 2512601 57 3 1246 163 403 0.404 46 130 0.354 117 273 0.429 0.462 58 84 0.690 18 86 104 183 47 4 66 84 430 0.345 0.047 0.003 0.147 0.038 0.053 0.037 7.544 3.211 1.825
Spencer Dinwiddie PG 25 BRK 1656092 68 4 1914 366 828 0.442 124 370 0.335 242 458 0.528 0.517 287 356 0.806 26 140 166 311 40 17 152 187 1143 0.597 0.150 0.009 0.162 0.021 0.079 0.065 16.809 4.574 2.441
Stephen Curry PG 30 GSW 37457154 69 69 2331 632 1340 0.472 354 810 0.437 278 530 0.525 0.604 263 287 0.916 45 324 369 361 92 25 192 166 1881 0.807 0.113 0.011 0.155 0.039 0.082 0.152 27.261 5.232 5.348
Terry Rozier PG 24 BOS 3050389 79 14 1791 258 666 0.387 119 337 0.353 139 329 0.422 0.477 73 93 0.785 32 275 307 231 68 21 68 101 708 0.395 0.041 0.012 0.129 0.038 0.038 0.066 8.962 2.924 3.886
Tim Frazier PG 28 TOT 1832107 59 19 1120 116 261 0.444 37 101 0.366 79 160 0.494 0.515 41 54 0.759 41 127 168 248 30 5 76 112 310 0.277 0.037 0.004 0.221 0.027 0.068 0.033 5.254 4.203 2.847
Tony Parker PG 36 CHO 5000000 56 0 1003 213 463 0.460 13 51 0.255 200 412 0.485 0.474 91 124 0.734 14 69 83 207 21 7 75 53 530 0.528 0.091 0.007 0.206 0.021 0.075 0.013 9.464 3.696 1.482
Trae Young PG 20 ATL 5363280 81 81 2503 525 1256 0.418 156 482 0.324 369 774 0.477 0.480 343 414 0.829 64 237 301 653 72 15 308 140 1549 0.619 0.137 0.006 0.261 0.029 0.123 0.062 19.123 8.062 3.716
Trey Burke PG 26 TOT 1795015 58 8 1125 236 548 0.431 56 159 0.352 180 389 0.463 0.482 103 124 0.831 28 71 99 159 33 7 49 58 631 0.561 0.092 0.006 0.141 0.029 0.044 0.050 10.879 2.741 1.707
Tyler Johnson PG 26 TOT 19245370 57 22 1529 217 526 0.413 90 260 0.346 127 266 0.477 0.498 95 127 0.748 34 139 173 166 54 27 77 97 619 0.405 0.062 0.018 0.109 0.035 0.050 0.059 10.860 2.912 3.035
Tyrone Wallace PG 24 LAC 1349383 62 0 628 92 217 0.424 4 19 0.211 88 198 0.444 0.433 30 57 0.526 20 81 101 42 21 7 36 83 218 0.347 0.048 0.011 0.067 0.033 0.057 0.006 3.516 0.677 1.629
Tyus Jones PG 22 MIN 2444052 68 23 1560 185 446 0.415 40 126 0.317 145 320 0.453 0.460 58 69 0.841 23 111 134 327 81 5 47 78 468 0.300 0.037 0.003 0.210 0.052 0.030 0.026 6.882 4.809 1.971
Yogi Ferrell PG 25 SAC 3000000 71 3 1067 153 352 0.435 54 149 0.362 99 203 0.488 0.511 60 67 0.896 13 96 109 137 36 4 40 64 420 0.394 0.056 0.004 0.128 0.034 0.037 0.051 5.915 1.930 1.535
Abdel Nader SF 25 OKC 1378242 61 1 694 91 215 0.423 32 100 0.320 59 115 0.513 0.498 27 36 0.750 14 102 116 20 20 12 26 68 241 0.347 0.039 0.017 0.029 0.029 0.037 0.046 3.951 0.328 1.902
Alfonzo McKinnie SF 26 GSW 1349383 72 5 1003 134 275 0.487 42 118 0.356 92 157 0.586 0.564 27 48 0.563 81 166 247 31 18 15 30 134 337 0.336 0.027 0.015 0.031 0.018 0.030 0.042 4.681 0.431 3.431
Andre Iguodala SF 35 GSW 16000000 68 13 1578 151 302 0.500 48 144 0.333 103 158 0.652 0.579 39 67 0.582 48 204 252 216 61 51 52 95 389 0.247 0.025 0.032 0.137 0.039 0.033 0.030 5.721 3.176 3.706
Andrew Wiggins SF 23 MIN 25467250 73 73 2543 498 1209 0.412 118 348 0.339 380 861 0.441 0.461 207 296 0.699 83 269 352 184 70 48 138 153 1321 0.519 0.081 0.019 0.072 0.028 0.054 0.046 18.096 2.521 4.822
Brandon Ingram SF 21 LAL 5757120 52 52 1760 362 729 0.497 31 94 0.330 331 635 0.521 0.518 195 289 0.675 41 226 267 154 28 31 129 149 950 0.540 0.111 0.018 0.088 0.016 0.073 0.018 18.269 2.962 5.135
Bruno Caboclo SF 23 MEM 705361 34 19 800 96 225 0.427 48 130 0.369 48 95 0.505 0.533 42 50 0.840 42 116 158 50 14 33 38 81 282 0.352 0.052 0.041 0.062 0.018 0.048 0.060 8.294 1.471 4.647
Caris LeVert SF 24 BRK 1702800 40 25 1063 207 483 0.429 48 154 0.312 159 329 0.483 0.478 85 123 0.691 35 116 151 156 42 14 69 77 547 0.515 0.080 0.013 0.147 0.040 0.065 0.045 13.675 3.900 3.775
Cedi Osman SF 23 CLE 2775000 76 75 2444 360 844 0.427 130 374 0.348 230 470 0.489 0.504 141 181 0.779 45 312 357 195 60 11 114 195 991 0.405 0.058 0.005 0.080 0.025 0.047 0.053 13.039 2.566 4.697
Chandler Hutchison SF 22 CHI 1991520 44 14 895 96 209 0.459 14 50 0.280 82 159 0.516 0.493 23 38 0.605 31 154 185 34 23 6 25 59 229 0.256 0.026 0.007 0.038 0.026 0.028 0.016 5.205 0.773 4.205
Chandler Parsons SF 30 MEM 24107258 25 3 496 68 182 0.374 29 94 0.309 39 88 0.443 0.453 22 25 0.880 4 66 70 43 19 5 32 45 187 0.377 0.044 0.010 0.087 0.038 0.065 0.058 7.480 1.720 2.800
Corey Brewer SF 32 TOT 2559925 31 3 492 53 123 0.431 14 44 0.318 39 79 0.494 0.488 31 43 0.721 26 50 76 39 32 7 19 63 151 0.307 0.063 0.014 0.079 0.065 0.039 0.028 4.871 1.258 2.452
Danilo Gallinari SF 30 LAC 21587579 68 68 2059 409 884 0.463 161 372 0.433 248 512 0.484 0.554 367 406 0.904 54 363 417 178 49 23 99 129 1346 0.654 0.178 0.011 0.086 0.024 0.048 0.078 19.794 2.618 6.132
Danuel House SF 25 HOU 247827 39 13 979 118 252 0.468 74 178 0.416 44 74 0.595 0.615 56 71 0.789 25 115 140 40 21 11 35 80 366 0.374 0.057 0.011 0.041 0.021 0.036 0.076 9.385 1.026 3.590
Darius Miller SF 28 NOP 2205000 69 15 1757 189 484 0.390 133 364 0.365 56 120 0.467 0.528 56 71 0.789 14 114 128 146 40 23 59 165 567 0.323 0.032 0.013 0.083 0.023 0.034 0.076 8.217 2.116 1.855
Derrick Jones SF 21 MIA 1512601 60 14 1153 160 324 0.494 28 91 0.308 132 233 0.567 0.537 74 122 0.607 96 144 240 37 46 42 43 123 422 0.366 0.064 0.036 0.032 0.040 0.037 0.024 7.033 0.617 4.000
Dorian Finney-Smith SF 25 DAL 1544951 81 26 1985 228 528 0.432 79 254 0.311 149 274 0.544 0.507 73 103 0.709 138 251 389 95 69 36 74 186 608 0.306 0.037 0.018 0.048 0.035 0.037 0.040 7.506 1.173 4.802
Doug McDermott SF 27 IND 7333334 77 1 1340 207 422 0.491 84 206 0.408 123 216 0.569 0.590 66 79 0.835 17 92 109 67 18 8 42 104 564 0.421 0.049 0.006 0.050 0.013 0.031 0.063 7.325 0.870 1.416
Glenn Robinson SF 25 DET 4075000 47 18 610 74 176 0.420 18 62 0.290 56 114 0.491 0.472 32 40 0.800 17 54 71 21 14 8 18 45 198 0.325 0.052 0.013 0.034 0.023 0.030 0.030 4.213 0.447 1.511
Jae Crowder SF 28 UTA 7305825 80 11 2166 318 797 0.399 173 522 0.331 145 275 0.527 0.508 142 197 0.721 60 324 384 133 64 31 85 170 951 0.439 0.066 0.014 0.061 0.030 0.039 0.080 11.887 1.663 4.800
Jake Layman SF 24 POR 1544951 71 33 1327 216 424 0.509 59 181 0.326 157 243 0.646 0.579 50 71 0.704 56 161 217 53 31 30 46 116 541 0.408 0.038 0.023 0.040 0.023 0.035 0.044 7.620 0.746 3.056
James Ennis SF 28 TOT 1621415 58 27 1230 138 294 0.469 55 156 0.353 83 138 0.601 0.563 58 81 0.716 60 122 182 41 41 23 34 150 389 0.316 0.047 0.019 0.033 0.033 0.028 0.045 6.707 0.707 3.138
Jaron Blossomgame SF 25 CLE 77250 27 4 439 47 106 0.443 10 39 0.256 37 67 0.552 0.491 10 13 0.769 26 72 98 13 7 8 11 20 114 0.260 0.023 0.018 0.030 0.016 0.025 0.023 4.222 0.481 3.630
Jayson Tatum SF 20 BOS 6700800 79 79 2455 466 1036 0.450 116 311 0.373 350 725 0.483 0.506 195 228 0.855 70 407 477 168 84 57 122 168 1243 0.506 0.079 0.023 0.068 0.034 0.050 0.047 15.734 2.127 6.038
Justin Anderson SF 25 ATL 2516047 48 4 463 64 157 0.408 24 77 0.312 40 80 0.500 0.484 26 35 0.743 24 60 84 23 22 13 23 48 178 0.384 0.056 0.028 0.050 0.048 0.050 0.052 3.708 0.479 1.750
Justin Jackson SF 23 TOT 2807880 81 14 1614 217 485 0.447 87 245 0.355 130 240 0.542 0.537 62 79 0.785 44 168 212 96 32 14 29 99 583 0.361 0.038 0.009 0.059 0.020 0.018 0.054 7.198 1.185 2.617
Justise Winslow SF 22 MIA 3448926 66 52 1959 324 749 0.433 96 256 0.375 228 493 0.462 0.497 86 137 0.628 63 292 355 282 72 19 142 177 830 0.424 0.044 0.010 0.144 0.037 0.072 0.049 12.576 4.273 5.379
Kawhi Leonard SF 27 TOR 23114066 60 60 2040 560 1129 0.496 112 302 0.371 448 827 0.542 0.546 364 426 0.854 78 361 439 199 106 24 121 87 1596 0.782 0.178 0.012 0.098 0.052 0.059 0.055 26.600 3.317 7.317
Keita Bates-Diop SF 23 MIN 838464 30 3 503 60 142 0.423 13 52 0.250 47 90 0.522 0.468 18 28 0.643 16 67 83 17 18 14 14 29 151 0.300 0.036 0.028 0.034 0.036 0.028 0.026 5.033 0.567 2.767
Kelly Oubre SF 23 TOT 3208630 69 19 1935 375 842 0.445 108 338 0.320 267 504 0.530 0.510 189 244 0.775 71 254 325 84 84 59 103 181 1047 0.541 0.098 0.030 0.043 0.043 0.053 0.056 15.174 1.217 4.710
Kenrich Williams SF 24 NOP 838464 46 29 1079 107 279 0.384 52 156 0.333 55 123 0.447 0.477 13 19 0.684 55 164 219 83 45 19 36 95 279 0.259 0.012 0.018 0.077 0.042 0.033 0.048 6.065 1.804 4.761
Kevin Durant SF 30 GSW 30000000 78 78 2702 721 1383 0.521 137 388 0.353 584 995 0.587 0.571 448 506 0.885 33 464 497 457 58 84 225 155 2027 0.750 0.166 0.031 0.169 0.021 0.083 0.051 25.987 5.859 6.372
Khris Middleton SF 27 MIL 13000000 77 77 2393 506 1148 0.441 179 474 0.378 327 674 0.485 0.519 216 258 0.837 50 411 461 331 80 7 174 172 1407 0.588 0.090 0.003 0.138 0.033 0.073 0.075 18.273 4.299 5.987
Kyle Anderson SF 25 MEM 8641000 43 40 1281 150 276 0.543 9 34 0.265 141 242 0.583 0.560 37 64 0.578 48 203 251 128 54 37 58 112 346 0.270 0.029 0.029 0.100 0.042 0.045 0.007 8.047 2.977 5.837
LeBron James SF 34 LAL 35654150 55 55 1937 558 1095 0.510 111 327 0.339 447 768 0.582 0.560 278 418 0.665 57 408 465 454 72 33 197 94 1505 0.777 0.144 0.017 0.234 0.037 0.102 0.057 27.364 8.255 8.455
Luol Deng SF 33 MIN 16747954 22 2 392 59 118 0.500 14 44 0.318 45 74 0.608 0.559 25 35 0.714 20 53 73 18 15 8 14 24 157 0.401 0.064 0.020 0.046 0.038 0.036 0.036 7.136 0.818 3.318
Mario Hezonja SF 23 NYK 6500000 58 24 1206 191 464 0.412 42 152 0.276 149 312 0.478 0.457 87 114 0.763 28 211 239 88 57 8 88 110 511 0.424 0.072 0.007 0.073 0.047 0.073 0.035 8.810 1.517 4.121
Mikal Bridges SF 22 PHO 3557400 82 56 2417 242 563 0.430 105 313 0.335 137 250 0.548 0.523 95 118 0.805 56 208 264 173 129 38 70 201 684 0.283 0.039 0.016 0.072 0.053 0.029 0.043 8.341 2.110 3.220
Miles Bridges SF 20 CHO 3206640 80 25 1696 237 511 0.464 65 200 0.325 172 311 0.553 0.527 58 77 0.753 67 256 323 95 55 49 50 111 597 0.352 0.034 0.029 0.056 0.032 0.029 0.038 7.463 1.188 4.037
Nicolas Batum SF 30 CHO 24000000 75 72 2354 253 562 0.450 116 298 0.389 137 264 0.519 0.553 77 89 0.865 71 319 390 247 71 43 117 140 699 0.297 0.033 0.018 0.105 0.030 0.050 0.049 9.320 3.293 5.200
OG Anunoby SF 21 TOR 1952760 67 6 1352 183 404 0.453 67 202 0.332 116 202 0.574 0.536 36 62 0.581 58 139 197 47 46 22 55 140 469 0.347 0.027 0.016 0.035 0.034 0.041 0.050 7.000 0.701 2.940
Omri Casspi SF 30 MEM 2176260 36 0 520 86 161 0.534 15 43 0.349 71 118 0.602 0.581 39 58 0.672 17 98 115 26 20 9 23 35 226 0.435 0.075 0.017 0.050 0.038 0.044 0.029 6.278 0.722 3.194
Otto Porter SF 25 TOT 26011913 56 43 1683 299 643 0.465 104 256 0.406 195 387 0.504 0.546 78 96 0.813 54 260 314 120 82 31 65 108 780 0.463 0.046 0.018 0.071 0.049 0.039 0.062 13.929 2.143 5.607
Paul George SF 28 OKC 30560700 77 77 2841 707 1614 0.438 292 757 0.386 415 857 0.484 0.529 453 540 0.839 105 523 628 318 170 34 205 214 2159 0.760 0.159 0.012 0.112 0.060 0.072 0.103 28.039 4.130 8.156
Quincy Pondexter SF 30 SAS 2165481 53 0 292 29 58 0.500 6 18 0.333 23 40 0.575 0.552 34 42 0.810 8 38 46 24 11 1 13 24 98 0.336 0.116 0.003 0.082 0.038 0.045 0.021 1.849 0.453 0.868
Robert Covington SF 28 TOT 10464092 35 35 1203 156 362 0.431 85 225 0.378 71 137 0.518 0.548 68 89 0.764 28 165 193 46 74 47 47 126 465 0.387 0.057 0.039 0.038 0.062 0.039 0.071 13.286 1.314 5.514
Rodions Kurucs SF 20 BRK 1690000 63 46 1294 202 449 0.450 58 184 0.315 144 265 0.543 0.514 72 92 0.783 56 190 246 52 41 25 77 146 534 0.413 0.056 0.019 0.040 0.032 0.060 0.045 8.476 0.825 3.905
Rondae Hollis-Jefferson SF 24 BRK 2470356 59 21 1234 200 487 0.411 9 49 0.184 191 438 0.436 0.420 118 183 0.645 83 227 310 96 44 27 68 107 527 0.427 0.096 0.022 0.078 0.036 0.055 0.007 8.932 1.627 5.254
Royce O’Neale SF 25 UTA 1378242 82 16 1671 163 343 0.475 68 176 0.386 95 167 0.569 0.574 32 42 0.762 22 263 285 124 54 24 70 172 426 0.255 0.019 0.014 0.074 0.032 0.042 0.041 5.195 1.512 3.476
Solomon Hill SF 27 NOP 12763467 44 15 878 68 178 0.382 32 101 0.317 36 77 0.468 0.472 23 32 0.719 34 99 133 55 23 10 31 80 191 0.218 0.026 0.011 0.063 0.026 0.035 0.036 4.341 1.250 3.023
Stanley Johnson SF 22 TOT 3940401 66 7 1208 171 440 0.389 62 215 0.288 109 225 0.484 0.459 50 64 0.781 34 183 217 88 60 14 81 114 454 0.376 0.041 0.012 0.073 0.050 0.067 0.051 6.879 1.333 3.288
Sviatoslav Mykhailiuk SF 21 TOT 1487694 42 0 440 46 140 0.329 29 89 0.326 17 51 0.333 0.432 12 20 0.600 9 27 36 37 14 1 21 25 133 0.302 0.027 0.002 0.084 0.032 0.048 0.066 3.167 0.881 0.857
Thabo Sefolosha SF 34 UTA 5250000 50 2 609 71 149 0.477 34 78 0.436 37 71 0.521 0.591 14 22 0.636 8 115 123 27 43 5 25 41 190 0.312 0.023 0.008 0.044 0.071 0.041 0.056 3.800 0.540 2.460
Tony Snell SF 27 MIL 10607143 74 12 1304 163 361 0.452 81 204 0.397 82 157 0.522 0.564 37 42 0.881 29 128 157 68 26 18 23 90 444 0.340 0.028 0.014 0.052 0.020 0.018 0.062 6.000 0.919 2.122
Torrey Craig SF 28 DEN 2000000 75 37 1503 160 362 0.442 61 188 0.324 99 174 0.569 0.526 49 70 0.700 89 174 263 72 37 46 44 175 430 0.286 0.033 0.031 0.048 0.025 0.029 0.041 5.733 0.960 3.507
Trevor Ariza SF 33 TOT 15000000 69 69 2349 294 736 0.399 145 434 0.334 149 302 0.493 0.498 130 164 0.793 50 321 371 252 91 21 106 130 863 0.367 0.055 0.009 0.107 0.039 0.045 0.062 12.507 3.652 5.377
Troy Brown SF 19 WAS 2752680 52 10 730 97 234 0.415 22 69 0.319 75 165 0.455 0.462 32 47 0.681 35 110 145 80 21 5 30 56 248 0.340 0.044 0.007 0.110 0.029 0.041 0.030 4.769 1.538 2.788
Troy Williams SF 24 SAC 77250 21 0 312 44 98 0.449 14 44 0.318 30 54 0.556 0.520 9 15 0.600 12 47 59 11 10 8 9 37 111 0.356 0.029 0.026 0.035 0.032 0.029 0.045 5.286 0.524 2.810
Wesley Iwundu SF 24 ORL 1378242 68 13 1233 113 274 0.412 29 79 0.367 84 195 0.431 0.465 84 103 0.816 37 147 184 73 28 22 44 123 339 0.275 0.068 0.018 0.059 0.023 0.036 0.024 4.985 1.074 2.706
Wesley Johnson SF 31 TOT 6134000 38 13 534 45 128 0.352 25 76 0.329 20 52 0.385 0.449 13 19 0.684 12 60 72 23 14 12 18 63 128 0.240 0.024 0.022 0.043 0.026 0.034 0.047 3.368 0.605 1.895
Jimmy Butler SF-SG 29 TOT 19841627 65 65 2185 418 904 0.462 67 193 0.347 351 711 0.494 0.499 312 365 0.855 121 221 342 263 123 39 95 111 1215 0.556 0.143 0.018 0.120 0.056 0.043 0.031 18.692 4.046 5.262
Wesley Matthews SF-SG 32 TOT 19360228 69 68 2091 279 698 0.400 150 403 0.372 129 295 0.437 0.507 132 163 0.810 32 138 170 160 54 17 91 160 840 0.402 0.063 0.008 0.077 0.026 0.044 0.072 12.174 2.319 2.464
Alec Burks SG 27 TOT 11536515 64 24 1375 192 474 0.405 61 168 0.363 131 306 0.428 0.469 116 141 0.823 30 205 235 128 39 21 65 91 561 0.408 0.084 0.015 0.093 0.028 0.047 0.044 8.766 2.000 3.672
Alex Abrines SG 25 OKC 3667645 31 2 588 56 157 0.357 41 127 0.323 15 30 0.500 0.487 12 13 0.923 5 43 48 20 17 6 14 53 165 0.281 0.020 0.010 0.034 0.029 0.024 0.070 5.323 0.645 1.548
Allen Crabbe SG 26 BRK 19332500 43 20 1133 137 373 0.367 98 259 0.378 39 114 0.342 0.499 41 56 0.732 16 132 148 46 23 13 46 102 413 0.365 0.036 0.011 0.041 0.020 0.041 0.086 9.605 1.070 3.442
Allonzo Trier SG 23 NYK 3382000 64 3 1459 232 518 0.448 52 132 0.394 180 386 0.466 0.498 179 223 0.803 31 166 197 119 28 14 116 117 695 0.476 0.123 0.010 0.082 0.019 0.080 0.036 10.859 1.859 3.078
Anfernee Simons SG 19 POR 1837800 20 1 141 28 63 0.444 10 29 0.345 18 34 0.529 0.524 9 16 0.563 3 10 13 13 1 0 11 9 75 0.532 0.064 0.000 0.092 0.007 0.078 0.071 3.750 0.650 0.650
Antonio Blakeney SG 22 CHI 1349383 57 3 829 166 396 0.419 36 91 0.396 130 305 0.426 0.465 50 76 0.658 7 99 106 42 12 9 35 41 418 0.504 0.060 0.011 0.051 0.014 0.042 0.043 7.333 0.737 1.860
Austin Rivers SG 26 TOT 13155324 76 15 2028 232 572 0.406 104 327 0.318 128 245 0.522 0.497 50 95 0.526 25 137 162 167 47 23 68 207 618 0.305 0.025 0.011 0.082 0.023 0.034 0.051 8.132 2.197 2.132
Avery Bradley SG 28 TOT 12000000 63 63 1905 248 608 0.408 86 245 0.351 162 363 0.446 0.479 43 50 0.860 43 132 175 152 41 16 89 167 625 0.328 0.023 0.008 0.080 0.022 0.047 0.045 9.921 2.413 2.778
Bradley Beal SG 25 WAS 25434262 82 82 3028 764 1609 0.475 209 596 0.351 555 1013 0.548 0.540 362 448 0.808 89 322 411 448 121 58 224 226 2099 0.693 0.120 0.019 0.148 0.040 0.074 0.069 25.598 5.463 5.012
Bruce Brown SG 22 DET 838464 74 56 1449 125 314 0.398 24 93 0.258 101 221 0.457 0.436 45 60 0.750 48 137 185 91 40 36 46 178 319 0.220 0.031 0.025 0.063 0.028 0.032 0.017 4.311 1.230 2.500
Bryn Forbes SG 25 SAS 3125000 82 81 2293 361 791 0.456 176 413 0.426 185 378 0.489 0.568 69 78 0.885 18 221 239 175 45 4 80 159 967 0.422 0.030 0.002 0.076 0.020 0.035 0.077 11.793 2.134 2.915
Buddy Hield SG 26 SAC 3833760 82 82 2615 623 1360 0.458 278 651 0.427 345 709 0.487 0.560 171 193 0.886 106 306 412 205 58 33 146 202 1695 0.648 0.065 0.013 0.078 0.022 0.056 0.106 20.671 2.500 5.024
CJ McCollum SG 27 POR 25759766 70 70 2375 571 1243 0.459 167 445 0.375 404 798 0.506 0.527 159 192 0.828 62 220 282 207 55 28 106 172 1468 0.618 0.067 0.012 0.087 0.023 0.045 0.070 20.971 2.957 4.029
Courtney Lee SG 33 TOT 12253780 34 6 428 53 129 0.411 16 55 0.291 37 74 0.500 0.473 14 21 0.667 9 45 54 37 21 3 14 32 136 0.318 0.033 0.007 0.086 0.049 0.033 0.037 4.000 1.088 1.588
Damion Lee SG 26 GSW 77250 32 0 375 56 127 0.441 27 68 0.397 29 59 0.492 0.547 19 22 0.864 8 56 64 13 13 0 11 28 158 0.421 0.051 0.000 0.035 0.035 0.029 0.072 4.938 0.406 2.000
Damyean Dotson SG 24 NYK 1378242 73 40 2004 290 698 0.415 126 342 0.368 164 356 0.461 0.506 73 98 0.745 34 228 262 135 58 10 71 135 779 0.389 0.036 0.005 0.067 0.029 0.035 0.063 10.671 1.849 3.589
Danny Green SG 31 TOR 10000000 80 80 2216 293 630 0.465 198 435 0.455 95 195 0.487 0.622 37 44 0.841 60 257 317 126 73 53 75 171 821 0.370 0.017 0.024 0.057 0.033 0.034 0.089 10.262 1.575 3.962
David Nwaba SG 26 CLE 1512601 51 14 984 126 262 0.481 24 75 0.320 102 187 0.545 0.527 58 85 0.682 41 122 163 54 36 17 29 106 334 0.339 0.059 0.017 0.055 0.037 0.029 0.024 6.549 1.059 3.196
DeMar DeRozan SG 29 SAS 27739975 77 77 2688 631 1313 0.481 7 45 0.156 624 1268 0.492 0.483 366 441 0.830 54 408 462 475 86 36 199 177 1635 0.608 0.136 0.013 0.177 0.032 0.074 0.003 21.234 6.169 6.000
Deonte Burton SG 25 OKC 500000 32 0 240 33 82 0.402 8 27 0.296 25 55 0.455 0.451 8 12 0.667 4 24 28 9 6 8 9 31 82 0.342 0.033 0.033 0.038 0.025 0.038 0.033 2.562 0.281 0.875
Devin Booker SG 22 PHO 3314365 64 64 2242 586 1255 0.467 135 414 0.326 451 841 0.536 0.521 393 454 0.866 39 226 265 433 56 13 264 200 1700 0.758 0.175 0.006 0.193 0.025 0.118 0.060 26.562 6.766 4.141
Dion Waiters SG 27 MIA 12705000 44 28 1138 198 478 0.414 109 289 0.377 89 189 0.471 0.528 22 44 0.500 7 109 116 121 29 9 64 72 527 0.463 0.019 0.008 0.106 0.025 0.056 0.096 11.977 2.750 2.636
Donovan Mitchell SG 22 UTA 3111480 77 77 2598 661 1530 0.432 188 519 0.362 473 1011 0.468 0.493 319 396 0.806 59 257 316 322 106 31 218 208 1829 0.704 0.123 0.012 0.124 0.041 0.084 0.072 23.753 4.182 4.104
Donte DiVincenzo SG 22 MIL 2484360 27 0 411 50 124 0.403 22 83 0.265 28 41 0.683 0.492 9 12 0.750 16 49 65 31 13 6 19 38 131 0.319 0.022 0.015 0.075 0.032 0.046 0.054 4.852 1.148 2.407
Dwayne Bacon SG 23 CHO 1378242 43 13 759 122 257 0.475 38 87 0.437 84 170 0.494 0.549 34 46 0.739 8 81 89 47 12 5 18 72 316 0.416 0.045 0.007 0.062 0.016 0.024 0.050 7.349 1.093 2.070
Dwyane Wade SG 37 MIA 2393887 72 2 1885 416 960 0.433 86 261 0.330 330 699 0.472 0.478 165 233 0.708 69 216 285 301 59 38 166 118 1083 0.575 0.088 0.020 0.160 0.031 0.088 0.046 15.042 4.181 3.958
E’Twaun Moore SG 29 NOP 8808685 53 36 1463 256 532 0.481 76 176 0.432 180 356 0.506 0.553 45 59 0.763 35 92 127 102 40 8 59 112 633 0.433 0.031 0.005 0.070 0.027 0.040 0.052 11.943 1.925 2.396
Eric Gordon SG 30 HOU 13500375 68 53 2158 384 938 0.409 216 600 0.360 168 338 0.497 0.525 119 152 0.783 17 131 148 129 41 27 90 143 1103 0.511 0.055 0.013 0.060 0.019 0.042 0.100 16.221 1.897 2.176
Evan Fournier SG 26 ORL 17000000 81 81 2553 468 1069 0.438 153 450 0.340 315 619 0.509 0.509 137 170 0.806 38 220 258 295 71 12 154 225 1226 0.480 0.054 0.005 0.116 0.028 0.060 0.060 15.136 3.642 3.185
Furkan Korkmaz SG 21 PHI 1740000 48 7 679 98 245 0.400 47 144 0.326 51 101 0.505 0.496 36 44 0.818 16 91 107 52 29 2 25 62 279 0.411 0.053 0.003 0.077 0.043 0.037 0.069 5.812 1.083 2.229
Garrett Temple SG 32 TOT 8000000 75 55 2040 208 493 0.422 90 264 0.341 118 229 0.515 0.513 80 107 0.748 28 188 216 106 76 30 70 204 586 0.287 0.039 0.015 0.052 0.037 0.034 0.044 7.813 1.413 2.880
Gary Harris SG 24 DEN 16517857 57 48 1639 270 637 0.424 82 242 0.339 188 395 0.476 0.488 115 144 0.799 41 119 160 127 55 19 68 113 737 0.450 0.070 0.012 0.077 0.034 0.041 0.050 12.930 2.228 2.807
Gerald Green SG 33 HOU 1512601 73 0 1473 231 578 0.400 156 441 0.354 75 137 0.547 0.535 57 68 0.838 30 152 182 40 33 27 55 126 675 0.458 0.039 0.018 0.027 0.022 0.037 0.106 9.247 0.548 2.493
Grayson Allen SG 23 UTA 2076960 38 2 416 67 178 0.376 32 99 0.323 35 79 0.443 0.466 45 60 0.750 3 20 23 25 6 6 33 47 211 0.507 0.108 0.014 0.060 0.014 0.079 0.077 5.553 0.658 0.605
Hamidou Diallo SG 20 OKC 838464 51 3 526 75 165 0.455 4 24 0.167 71 141 0.504 0.467 36 59 0.610 38 59 97 17 21 10 23 77 190 0.361 0.068 0.019 0.032 0.040 0.044 0.008 3.725 0.333 1.902
Ian Clark SG 27 NOP 1757429 60 6 973 151 383 0.394 66 202 0.327 85 181 0.470 0.480 33 37 0.892 13 76 89 94 22 8 58 95 401 0.412 0.034 0.008 0.097 0.023 0.060 0.068 6.683 1.567 1.483
Iman Shumpert SG 28 TOT 11011234 62 41 1481 167 446 0.374 95 273 0.348 72 173 0.416 0.481 36 45 0.800 27 156 183 112 59 24 50 127 465 0.314 0.024 0.016 0.076 0.040 0.034 0.064 7.500 1.806 2.952
Jacob Evans SG 21 GSW 1646400 30 1 204 18 53 0.340 4 15 0.267 14 38 0.368 0.377 0 1 0.000 6 19 25 23 5 3 11 28 40 0.196 0.000 0.015 0.113 0.025 0.054 0.020 1.333 0.767 0.833
Jamal Crawford SG 38 PHO 4698113 64 0 1211 174 438 0.397 67 202 0.332 107 236 0.453 0.474 93 110 0.845 8 77 85 229 33 12 99 75 508 0.419 0.077 0.010 0.189 0.027 0.082 0.055 7.938 3.578 1.328
Jaylen Brown SG 22 BOS 5169960 74 25 1913 368 792 0.465 95 276 0.344 273 516 0.529 0.525 133 202 0.658 65 248 313 100 69 32 99 186 964 0.504 0.070 0.017 0.052 0.036 0.052 0.050 13.027 1.351 4.230
Jeremy Lamb SG 26 CHO 7000000 79 55 2250 431 979 0.440 115 330 0.348 316 649 0.487 0.499 231 260 0.888 65 369 434 172 88 32 80 140 1208 0.537 0.103 0.014 0.076 0.039 0.036 0.051 15.291 2.177 5.494
Jerome Robinson SG 21 LAC 3050160 33 0 320 44 110 0.400 18 57 0.316 26 53 0.491 0.482 6 9 0.667 3 38 41 19 11 3 13 46 112 0.350 0.019 0.009 0.059 0.034 0.041 0.056 3.394 0.576 1.242
Joe Harris SG 27 BRK 8333333 76 76 2293 374 748 0.500 183 386 0.474 191 362 0.528 0.622 110 133 0.827 52 239 291 181 38 17 121 182 1041 0.454 0.048 0.007 0.079 0.017 0.053 0.080 13.697 2.382 3.829
John Jenkins SG 27 TOT 585809 26 0 333 42 105 0.400 22 58 0.379 20 47 0.426 0.505 15 18 0.833 6 31 37 22 0 2 9 10 121 0.363 0.045 0.006 0.066 0.000 0.027 0.066 4.654 0.846 1.423
Jordan Clarkson SG 26 CLE 12500000 81 0 2214 529 1180 0.448 144 445 0.324 385 735 0.524 0.509 162 192 0.844 82 188 270 196 57 13 135 112 1364 0.616 0.073 0.006 0.089 0.026 0.061 0.065 16.840 2.420 3.333
Jordan McRae SG 27 WAS 77250 27 0 333 61 130 0.469 10 35 0.286 51 95 0.537 0.508 28 35 0.800 6 34 40 30 13 7 15 26 160 0.480 0.084 0.021 0.090 0.039 0.045 0.030 5.926 1.111 1.481
Josh Hart SG 23 LAL 1655160 67 22 1715 189 464 0.407 92 274 0.336 97 190 0.511 0.506 55 80 0.688 35 213 248 93 64 40 58 147 525 0.306 0.032 0.023 0.054 0.037 0.034 0.054 7.836 1.388 3.701
Josh Jackson SG 21 PHO 6041520 79 29 1988 347 841 0.413 73 225 0.324 274 616 0.445 0.456 143 213 0.671 66 281 347 183 74 56 173 209 910 0.458 0.072 0.028 0.092 0.037 0.087 0.037 11.519 2.316 4.392
Josh Okogie SG 20 MIN 2163600 74 52 1757 196 508 0.386 60 215 0.279 136 293 0.464 0.445 118 162 0.728 41 177 218 91 88 33 63 166 570 0.324 0.067 0.019 0.052 0.050 0.036 0.034 7.703 1.230 2.946
Josh Richardson SG 25 MIA 9367200 73 73 2539 423 1026 0.412 164 460 0.357 259 566 0.458 0.492 199 231 0.861 54 209 263 298 79 34 113 200 1209 0.476 0.078 0.013 0.117 0.031 0.045 0.065 16.562 4.082 3.603
Jrue Holiday SG 28 NOP 26641111 67 67 2402 547 1159 0.472 118 363 0.325 429 796 0.539 0.523 208 271 0.768 75 259 334 518 109 54 210 148 1420 0.591 0.087 0.022 0.216 0.045 0.087 0.049 21.194 7.731 4.985
Justin Holiday SG 29 TOT 4500000 82 77 2607 300 777 0.386 162 465 0.348 138 312 0.442 0.490 95 106 0.896 46 277 323 146 121 36 104 164 857 0.329 0.036 0.014 0.056 0.046 0.040 0.062 10.451 1.780 3.939
Kent Bazemore SG 29 ATL 18089888 67 35 1643 278 691 0.402 96 300 0.320 182 391 0.465 0.472 127 175 0.726 37 224 261 152 89 42 121 170 779 0.474 0.077 0.026 0.093 0.054 0.074 0.058 11.627 2.269 3.896
Kentavious Caldwell-Pope SG 25 LAL 12000000 82 23 2035 325 756 0.430 151 435 0.347 174 321 0.542 0.530 137 158 0.867 48 190 238 110 73 13 65 137 938 0.461 0.067 0.006 0.054 0.036 0.032 0.074 11.439 1.341 2.902
Kevin Huerter SG 20 ATL 2250960 75 59 2048 275 657 0.419 136 353 0.385 139 304 0.457 0.522 41 56 0.732 60 185 245 214 65 25 109 155 727 0.355 0.020 0.012 0.104 0.032 0.053 0.066 9.693 2.853 3.267
Khyri Thomas SG 22 DET 838464 26 0 195 22 69 0.319 10 35 0.286 12 34 0.353 0.391 7 11 0.636 4 16 20 8 7 5 4 22 61 0.313 0.036 0.026 0.041 0.036 0.021 0.051 2.346 0.308 0.769
Klay Thompson SG 28 GSW 18988725 78 78 2652 655 1402 0.467 241 599 0.402 414 803 0.516 0.553 129 158 0.816 37 262 299 186 84 47 115 157 1680 0.633 0.049 0.018 0.070 0.032 0.043 0.091 21.538 2.385 3.833
Lance Stephenson SG 28 LAL 4449000 68 3 1123 184 432 0.426 73 197 0.371 111 235 0.472 0.510 50 73 0.685 32 183 215 140 41 7 86 111 491 0.437 0.045 0.006 0.125 0.037 0.077 0.065 7.221 2.059 3.162
Landry Shamet SG 21 TOT 1705920 79 27 1802 240 557 0.431 167 396 0.422 73 161 0.453 0.581 75 93 0.806 21 113 134 117 37 10 45 155 722 0.401 0.042 0.006 0.065 0.021 0.025 0.093 9.139 1.481 1.696
Langston Galloway SG 27 DET 7000000 80 4 1745 228 587 0.388 135 380 0.355 93 207 0.449 0.503 81 96 0.844 49 122 171 85 37 8 24 135 672 0.385 0.046 0.005 0.049 0.021 0.014 0.077 8.400 1.062 2.138
Luke Kennard SG 22 DET 3275280 63 10 1437 228 520 0.438 106 269 0.394 122 251 0.486 0.540 51 61 0.836 12 171 183 114 26 10 57 92 613 0.427 0.035 0.007 0.079 0.018 0.040 0.074 9.730 1.810 2.905
Malachi Richardson SG 23 TOR 1569360 22 0 103 9 29 0.310 8 25 0.320 1 4 0.250 0.448 4 5 0.800 2 11 13 0 1 0 8 13 30 0.291 0.039 0.000 0.000 0.010 0.078 0.078 1.364 0.000 0.591
Malcolm Brogdon SG 26 MIL 1544951 64 64 1832 378 748 0.505 104 244 0.426 274 504 0.544 0.575 141 152 0.928 65 223 288 205 46 13 91 102 1001 0.546 0.077 0.007 0.112 0.025 0.050 0.057 15.641 3.203 4.500
Malik Beasley SG 22 DEN 1773840 81 18 1879 349 737 0.474 163 405 0.402 186 332 0.560 0.584 56 66 0.848 35 165 200 97 55 10 55 116 917 0.488 0.030 0.005 0.052 0.029 0.029 0.087 11.321 1.198 2.469
Malik Monk SG 20 CHO 3447480 73 0 1258 227 586 0.387 109 330 0.330 118 256 0.461 0.480 90 102 0.882 16 121 137 117 37 19 86 106 653 0.519 0.072 0.015 0.093 0.029 0.068 0.087 8.945 1.603 1.877
Marco Belinelli SG 32 SAS 6153846 79 1 1815 285 690 0.413 147 395 0.372 138 295 0.468 0.520 112 124 0.903 16 182 198 132 35 8 72 121 829 0.457 0.062 0.004 0.073 0.019 0.040 0.081 10.494 1.671 2.506
Marcus Smart SG 24 BOS 11160716 80 60 2200 239 567 0.422 126 346 0.364 113 221 0.511 0.533 104 129 0.806 57 177 234 321 143 28 123 201 708 0.322 0.047 0.013 0.146 0.065 0.056 0.057 8.850 4.013 2.925
MarShon Brooks SG 30 MEM 1656092 29 0 387 76 169 0.450 15 54 0.278 61 115 0.530 0.494 23 33 0.697 12 33 45 25 9 4 21 33 190 0.491 0.059 0.010 0.065 0.023 0.054 0.039 6.552 0.862 1.552
Nik Stauskas SG 25 TOT 2161886 68 0 1015 136 338 0.402 70 188 0.372 66 150 0.440 0.506 57 64 0.891 18 109 127 81 21 7 51 50 399 0.393 0.056 0.007 0.080 0.021 0.050 0.069 5.868 1.191 1.868
Norman Powell SG 25 TOR 9367200 60 3 1126 193 400 0.483 68 170 0.400 125 230 0.543 0.568 62 75 0.827 16 123 139 91 39 13 65 96 516 0.458 0.055 0.012 0.081 0.035 0.058 0.060 8.600 1.517 2.317
Pat Connaughton SG 26 MIL 1641000 61 2 1261 163 350 0.466 66 200 0.330 97 150 0.647 0.560 29 40 0.725 61 197 258 122 33 25 33 81 421 0.334 0.023 0.020 0.097 0.026 0.026 0.052 6.902 2.000 4.230
Patrick McCaw SG 23 TOT 964104 29 1 397 26 63 0.413 9 28 0.321 17 35 0.486 0.484 13 15 0.867 7 41 48 29 23 2 17 38 74 0.186 0.033 0.005 0.073 0.058 0.043 0.023 2.552 1.000 1.655
Reggie Bullock SG 27 TOT 2500000 63 60 1879 245 594 0.412 148 393 0.377 97 201 0.483 0.537 73 85 0.859 22 151 173 129 40 12 65 109 711 0.378 0.039 0.006 0.069 0.021 0.035 0.079 11.286 2.048 2.746
Rodney Hood SG 26 TOT 3472887 72 49 1893 292 671 0.435 84 236 0.356 208 435 0.478 0.498 137 155 0.884 25 132 157 126 59 12 55 146 805 0.425 0.072 0.006 0.067 0.031 0.029 0.044 11.181 1.750 2.181
Rodney McGruder SG 27 MIA 1544951 66 45 1550 186 461 0.403 79 225 0.351 107 236 0.453 0.489 52 72 0.722 60 178 238 112 36 12 64 115 503 0.325 0.034 0.008 0.072 0.023 0.041 0.051 7.621 1.697 3.606
Ryan Broekhoff SG 28 DAL 838464 42 0 453 57 126 0.452 38 93 0.409 19 33 0.576 0.603 15 19 0.789 8 55 63 22 6 4 16 35 167 0.369 0.033 0.009 0.049 0.013 0.035 0.084 3.976 0.524 1.500
Seth Curry SG 28 POR 2795000 74 2 1399 212 465 0.456 113 251 0.450 99 214 0.463 0.577 44 52 0.846 27 93 120 66 36 12 61 97 581 0.415 0.031 0.009 0.047 0.026 0.044 0.081 7.851 0.892 1.622
Shake Milton SG 22 PHI 77250 20 0 268 34 87 0.391 14 44 0.318 20 43 0.465 0.471 5 7 0.714 9 26 35 18 8 8 6 29 87 0.325 0.019 0.030 0.067 0.030 0.022 0.052 4.350 0.900 1.750
Sindarius Thornwell SG 24 LAC 1378242 64 1 313 17 49 0.347 3 15 0.200 14 34 0.412 0.378 25 34 0.735 5 39 44 18 14 7 20 41 62 0.198 0.080 0.022 0.058 0.045 0.064 0.010 0.969 0.281 0.688
Sterling Brown SG 23 MIL 1378242 58 7 1034 145 312 0.465 53 147 0.361 92 165 0.558 0.550 29 42 0.690 29 155 184 84 25 8 46 88 372 0.360 0.028 0.008 0.081 0.024 0.044 0.051 6.414 1.448 3.172
Terrance Ferguson SG 20 OKC 2118840 74 74 1931 185 431 0.429 106 290 0.366 79 141 0.560 0.552 37 51 0.725 33 108 141 72 40 16 47 231 513 0.266 0.019 0.008 0.037 0.021 0.024 0.055 6.932 0.973 1.905
Terrence Ross SG 27 ORL 10500000 81 0 2150 440 1027 0.428 217 566 0.383 223 461 0.484 0.534 126 144 0.875 27 253 280 135 72 29 90 119 1223 0.569 0.059 0.013 0.063 0.033 0.042 0.101 15.099 1.667 3.457
Tim Hardaway SG 26 TOT 17325000 65 63 2057 390 993 0.393 162 477 0.340 228 516 0.442 0.474 232 276 0.841 33 189 222 159 54 8 105 141 1174 0.571 0.113 0.004 0.077 0.026 0.051 0.079 18.062 2.446 3.415
Treveon Graham SG 25 BRK 1512601 35 21 715 64 191 0.335 38 128 0.297 26 63 0.413 0.435 18 22 0.818 23 84 107 34 13 7 17 68 184 0.257 0.025 0.010 0.048 0.018 0.024 0.053 5.257 0.971 3.057
Troy Daniels SG 27 PHO 3258539 51 1 760 113 275 0.411 74 194 0.381 39 81 0.481 0.545 18 23 0.783 13 60 73 26 26 5 27 79 318 0.418 0.024 0.007 0.034 0.034 0.036 0.097 6.235 0.510 1.431
Tyler Dorsey SG 22 TOT 1378242 48 11 698 107 264 0.405 44 132 0.333 63 132 0.477 0.489 38 61 0.623 27 86 113 56 14 2 27 53 296 0.424 0.054 0.003 0.080 0.020 0.039 0.063 6.167 1.167 2.354
Tyreke Evans SG 29 IND 12400000 69 18 1402 257 660 0.389 77 216 0.356 180 444 0.405 0.448 115 160 0.719 33 168 201 166 58 18 118 117 706 0.504 0.082 0.013 0.118 0.041 0.084 0.055 10.232 2.406 2.913
Victor Oladipo SG 26 IND 21000000 36 36 1147 249 588 0.423 74 216 0.343 175 372 0.470 0.486 103 141 0.730 21 181 202 186 60 11 82 72 675 0.588 0.090 0.010 0.162 0.052 0.071 0.065 18.750 5.167 5.611
Wayne Ellington SG 31 TOT 8653076 53 38 1297 184 457 0.403 138 372 0.371 46 85 0.541 0.554 39 49 0.796 14 93 107 72 54 6 40 92 545 0.420 0.030 0.005 0.056 0.042 0.031 0.106 10.283 1.358 2.019
Wayne Selden SG 24 TOT 1544951 75 13 1439 196 483 0.406 55 174 0.316 141 309 0.456 0.463 67 92 0.728 37 143 180 109 33 13 79 131 514 0.357 0.047 0.009 0.076 0.023 0.055 0.038 6.853 1.453 2.400
Will Barton SG 28 DEN 11830358 43 38 1189 185 460 0.402 67 196 0.342 118 264 0.447 0.475 57 74 0.770 32 167 199 124 18 22 65 82 494 0.415 0.048 0.019 0.104 0.015 0.055 0.056 11.488 2.884 4.628
Zach LaVine SG 23 CHI 19500000 63 62 2171 530 1135 0.467 120 321 0.374 410 814 0.504 0.520 312 375 0.832 40 254 294 283 60 26 215 140 1492 0.687 0.144 0.012 0.130 0.028 0.099 0.055 23.683 4.492 4.667
Kyle Korver SG-PF 37 TOT 7560000 70 0 1334 201 483 0.416 138 348 0.397 63 135 0.467 0.559 60 73 0.822 9 153 162 81 25 12 59 106 600 0.450 0.045 0.009 0.061 0.019 0.044 0.103 8.571 1.157 2.314
Jonathon Simmons SG-SF 29 TOT 6000000 56 9 1064 133 350 0.380 28 104 0.269 105 246 0.427 0.420 72 97 0.742 27 99 126 128 29 15 68 89 366 0.344 0.068 0.014 0.120 0.027 0.064 0.026 6.536 2.286 2.250

Explore various data models

Single Varible Linear Regression

Team Statistics Pace v Wins

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.08892848
## 
## Call:
## lm(formula = W ~ Pace, data = comb_team)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -23.7808  -7.1784   0.9702   8.7057  17.3618 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)   -9.220    106.323  -0.087    0.932
## Pace           0.502      1.063   0.472    0.640
## 
## Residual standard error: 12.19 on 28 degrees of freedom
## Multiple R-squared:  0.007908,   Adjusted R-squared:  -0.02752 
## F-statistic: 0.2232 on 1 and 28 DF,  p-value: 0.6403
##        1        2        3        4        5        6        7        8 
## 42.93945 40.78079 41.38320 40.32897 40.47958 39.27475 40.47958 39.82696 
##        9       10       11       12       13       14       15       16 
## 39.67636 41.43341 39.92736 40.02777 41.83502 42.58804 39.27475 40.07797 
##       17       18       19       20       21       22       23       24 
## 42.63824 41.08200 42.63824 40.78079 42.38723 40.02777 41.78482 41.23260 
##       25       26       27       28       29       30 
## 40.52978 42.53784 40.12817 41.08200 41.13220 41.68441

##  lag Autocorrelation D-W Statistic p-value
##    1       0.1024738      1.725845   0.428
##  Alternative hypothesis: rho != 0

Offence rating v Wins

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.8411322
## 
## Call:
## lm(formula = W ~ ORtg, data = comb_team)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -12.9184  -4.5433   0.0544   5.7203   8.6818 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -330.3378    45.1380  -7.318 5.73e-08 ***
## ORtg           3.3636     0.4087   8.230 5.88e-09 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6.621 on 28 degrees of freedom
## Multiple R-squared:  0.7075, Adjusted R-squared:  0.6971 
## F-statistic: 67.73 on 1 and 28 DF,  p-value: 5.882e-09
##        1        2        3        4        5        6        7        8 
## 33.26380 47.05442 38.30915 44.36357 22.16402 31.91837 37.63643 49.74527 
##        9       10       11       12       13       14       15       16 
## 36.29101 59.49962 58.15419 39.31822 47.72713 32.25473 26.53666 30.57294 
##       17       18       19       20       21       22       23       24 
## 52.43613 44.36357 44.36357 21.15495 40.66364 35.95465 48.39985 25.86395 
##       25       26       27       28       29       30 
## 55.46334 41.00000 49.40892 50.08163 42.68178 43.35450

##  lag Autocorrelation D-W Statistic p-value
##    1       0.1891721      1.501797   0.148
##  Alternative hypothesis: rho != 0

Defence rating v Wins

## `geom_smooth()` using formula 'y ~ x'

## [1] -0.7597828
## 
## Call:
## lm(formula = W ~ DRtg, data = comb_team)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -13.7612  -6.0172  -0.6127   6.1833  13.1944 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 383.8923    55.4715   6.921 1.60e-07 ***
## DRtg         -3.1058     0.5023  -6.184 1.12e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 7.959 on 28 degrees of freedom
## Multiple R-squared:  0.5773, Adjusted R-squared:  0.5622 
## F-statistic: 38.24 on 1 and 28 DF,  p-value: 1.118e-06
##        1        2        3        4        5        6        7        8 
## 30.14000 49.08547 43.18442 34.48814 32.31407 18.64849 40.07861 45.66907 
##        9       10       11       12       13       14       15       16 
## 44.73733 43.80559 40.07861 53.12303 37.59396 43.80559 45.97966 49.70663 
##       17       18       19       20       21       22       23       24 
## 57.16059 33.24582 34.17756 30.76117 51.57012 48.15373 42.25268 26.41303 
##       25       26       27       28       29       30 
## 40.69977 37.59396 38.52570 51.25954 55.60768 30.14000

##  lag Autocorrelation D-W Statistic p-value
##    1     -0.06302277      2.123362   0.818
##  Alternative hypothesis: rho != 0

3-Point Attempt Rating v Wins

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.2843269
## 
## Call:
## lm(formula = W ~ x3PAr, data = comb_team)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -22.2461  -6.4940  -0.6239  11.4337  15.5671 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)    15.59      16.33   0.955    0.348
## x3PAr          70.82      45.13   1.569    0.128
## 
## Residual standard error: 11.74 on 28 degrees of freedom
## Multiple R-squared:  0.08084,    Adjusted R-squared:  0.04801 
## F-statistic: 2.463 on 1 and 28 DF,  p-value: 0.1278
##        1        2        3        4        5        6        7        8 
## 44.13246 42.57449 44.13246 42.36204 36.48425 39.10447 45.47798 40.23754 
##        9       10       11       12       13       14       15       16 
## 43.49511 42.78694 52.34720 36.27180 36.48425 39.81264 39.81264 41.65387 
##       17       18       19       20       21       22       23       24 
## 45.26553 37.90059 38.53794 39.24611 40.16672 41.08734 39.81264 39.31692 
##       25       26       27       28       29       30 
## 39.60019 38.32549 35.84690 42.43286 43.49511 41.79551

##  lag Autocorrelation D-W Statistic p-value
##    1     0.009106348      1.897535   0.782
##  Alternative hypothesis: rho != 0

True Shooting Percentage v Wins

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.757103
## 
## Call:
## lm(formula = W ~ TSp, data = comb_team)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -17.4251  -5.4489   0.4241   5.1456  16.8073 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -297.32      55.19  -5.387 9.63e-06 ***
## TSp           604.62      98.60   6.132 1.28e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 7.997 on 28 degrees of freedom
## Multiple R-squared:  0.5732, Adjusted R-squared:  0.558 
## F-statistic: 37.61 on 1 and 28 DF,  p-value: 1.283e-06
##        1        2        3        4        5        6        7        8 
## 38.23891 45.49432 38.84353 37.63430 29.77427 29.16965 38.23891 40.05277 
##        9       10       11       12       13       14       15       16 
## 31.58812 63.02823 53.95897 41.86662 50.33126 37.63430 34.00659 30.37889 
##       17       18       19       20       21       22       23       24 
## 55.16820 36.42506 43.07585 22.51886 32.19274 35.21583 49.72665 36.42506 
##       25       26       27       28       29       30 
## 46.09894 37.63430 48.51741 52.74973 48.51741 45.49432

##  lag Autocorrelation D-W Statistic p-value
##    1       0.0368267         1.777   0.492
##  Alternative hypothesis: rho != 0

Effective Field Goal Percentage

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.7818644
## 
## Call:
## lm(formula = W ~ eFGp, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -15.728  -5.514   1.954   4.208  14.272 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -282.36      48.75  -5.792 3.21e-06 ***
## eFGp          616.90      92.96   6.636 3.36e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 7.632 on 28 degrees of freedom
## Multiple R-squared:  0.6113, Adjusted R-squared:  0.5974 
## F-statistic: 44.04 on 1 and 28 DF,  p-value: 3.365e-07
##        1        2        3        4        5        6        7        8 
## 39.66339 47.06617 38.42959 34.72820 29.17611 27.94231 37.81269 42.74788 
##        9       10       11       12       13       14       15       16 
## 31.64370 66.19003 52.00136 44.59858 43.98168 42.74788 31.02680 35.34510 
##       17       18       19       20       21       22       23       24 
## 56.93655 32.87750 43.98168 19.92263 34.72820 37.19579 45.83237 34.72820 
##       25       26       27       28       29       30 
## 43.36478 40.89718 47.06617 52.61826 49.53377 45.21547

##  lag Autocorrelation D-W Statistic p-value
##    1     -0.09648682      2.016169   0.958
##  Alternative hypothesis: rho != 0

Defensive Rebound Percentage v Lower Defensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] -0.5883396
## 
## Call:
## lm(formula = DRtg ~ DRBp, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.7577 -1.5538  0.1272  1.0524  7.1279 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 186.0914    19.6640   9.464  3.2e-10 ***
## DRBp         -0.9821     0.2551  -3.850 0.000627 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.422 on 28 degrees of freedom
## Multiple R-squared:  0.3461, Adjusted R-squared:  0.3228 
## F-statistic: 14.82 on 1 and 28 DF,  p-value: 0.0006273
##        1        2        3        4        5        6        7        8 
## 111.0613 110.4721 111.0613 110.3739 110.1775 110.4721 109.9810 109.4900 
##        9       10       11       12       13       14       15       16 
## 108.8026 110.3739 113.0255 111.2577 111.4541 111.0613 109.8828 109.8828 
##       17       18       19       20       21       22       23       24 
## 107.2313 112.5344 110.6685 111.3559 109.2936 107.8205 108.9008 114.8914 
##       25       26       27       28       29       30 
## 109.5882 111.9452 108.1151 110.3739 107.2313 113.3201

##  lag Autocorrelation D-W Statistic p-value
##    1        0.233268      1.482338   0.154
##  Alternative hypothesis: rho != 0

Turnover Totals contributing to Losses

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.2471353
## 
## Call:
## lm(formula = L ~ TOV, data = comb_team)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -18.3705  -9.4752  -0.2251   7.5361  24.1344 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)  0.16303   30.33643   0.005    0.996
## TOV          0.03536    0.02620   1.350    0.188
## 
## Residual standard error: 11.86 on 28 degrees of freedom
## Multiple R-squared:  0.06108,    Adjusted R-squared:  0.02754 
## F-statistic: 1.821 on 1 and 28 DF,  p-value: 0.188
##        1        2        3        4        5        6        7        8 
## 49.56487 37.36470 43.87146 35.56120 41.14852 39.27429 41.43143 39.13284 
##        9       10       11       12       13       14       15       16 
## 40.29982 41.50215 38.84994 39.84010 42.35086 45.56888 40.72417 42.88130 
##       17       18       19       20       21       22       23       24 
## 40.37054 38.14268 43.12884 40.86562 40.65344 38.42559 43.41174 45.39206 
##       25       26       27       28       29       30 
## 40.29982 38.88530 35.24293 40.83026 44.01291 40.97171

##  lag Autocorrelation D-W Statistic p-value
##    1      0.09567978      1.784956   0.584
##  Alternative hypothesis: rho != 0

Net Rating v Wins

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.9800362
## 
## Call:
## lm(formula = W ~ NRtg, data = comb_team)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -5.099 -1.440  0.325  1.697  4.810 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 41.00808    0.44436   92.28   <2e-16 ***
## NRtg         2.42414    0.09294   26.08   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.434 on 28 degrees of freedom
## Multiple R-squared:  0.9605, Adjusted R-squared:  0.9591 
## F-statistic: 680.3 on 1 and 28 DF,  p-value: < 2.2e-16
##        1        2        3        4        5        6        7        8 
## 26.94806 51.67431 40.76567 38.34152 20.64529 17.00907 37.85670 50.94706 
##        9       10       11       12       13       14       15       16 
## 40.52325 56.52259 52.64396 49.25016 43.18981 36.88704 34.46290 40.28084 
##       17       18       19       20       21       22       23       24 
## 61.85570 37.37187 38.09911 18.70597 49.00775 42.94739 47.31085 18.70597 
##       25       26       27       28       29       30 
## 51.18948 38.34152 45.12912 55.55293 53.61362 34.22048

##  lag Autocorrelation D-W Statistic p-value
##    1      -0.0192226      1.983334   0.898
##  Alternative hypothesis: rho != 0

Total Points contributing to Offensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.6606001
## 
## Call:
## lm(formula = W ~ PTS, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -16.215  -7.302   1.969   6.859  14.044 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -1.749e+02  4.641e+01  -3.770 0.000776 ***
## PTS          2.368e-02  5.086e-03   4.656  7.1e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9.19 on 28 degrees of freedom
## Multiple R-squared:  0.4364, Adjusted R-squared:  0.4163 
## F-statistic: 21.68 on 1 and 28 DF,  p-value: 7.098e-05
##        1        2        3        4        5        6        7        8 
## 45.14174 43.29465 43.01048 40.09777 28.82580 27.92594 36.45096 39.95569 
##        9       10       11       12       13       14       15       16 
## 32.92255 53.57203 46.25473 34.79331 48.64647 42.08694 26.10253 30.31768 
##       17       18       19       20       21       22       23       24 
## 54.42453 43.46041 49.21480 28.11538 47.34403 33.44352 48.71751 33.79873 
##       25       26       27       28       29       30 
## 47.69924 46.77570 41.87381 47.27299 41.99222 46.46785

##  lag Autocorrelation D-W Statistic p-value
##    1       0.1627497      1.475814   0.132
##  Alternative hypothesis: rho != 0

Three points v Wins

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.4838773
## 
## Call:
## lm(formula = W ~ x3P, data = comb_team)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -18.8669  -5.9449  -0.9138  10.2949  14.3599 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept) -2.94961   15.14840  -0.195  0.84702   
## x3P          0.04716    0.01612   2.926  0.00674 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 10.71 on 28 degrees of freedom
## Multiple R-squared:  0.2341, Adjusted R-squared:  0.2068 
## F-statistic:  8.56 on 1 and 28 DF,  p-value: 0.006744
##        1        2        3        4        5        6        7        8 
## 47.37509 45.72433 46.43180 43.13027 32.18807 36.99886 45.25268 39.64009 
##        9       10       11       12       13       14       15       16 
## 43.88491 48.31838 59.44925 33.79167 35.77258 36.99886 35.30094 40.81920 
##       17       18       19       20       21       22       23       24 
## 49.16735 36.05557 36.76304 35.86691 41.00786 41.24368 38.97978 34.31048 
##       25       26       27       28       29       30 
## 39.68725 40.77204 35.34810 44.92253 43.88491 40.91353

##  lag Autocorrelation D-W Statistic p-value
##    1     -0.04675096       1.96371   0.932
##  Alternative hypothesis: rho != 0

Two points v Wins

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.06870566
## 
## Call:
## lm(formula = W ~ x2P, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -23.416  -7.210   1.202   9.174  18.939 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)
## (Intercept) 29.701338  31.084806   0.955    0.348
## x2P          0.004636   0.012723   0.364    0.718
## 
## Residual standard error: 12.21 on 28 degrees of freedom
## Multiple R-squared:  0.00472,    Adjusted R-squared:  -0.03083 
## F-statistic: 0.1328 on 1 and 28 DF,  p-value: 0.7183
##        1        2        3        4        5        6        7        8 
## 40.48118 40.91701 40.15199 40.45799 41.38993 40.56000 39.71616 41.45948 
##        9       10       11       12       13       14       15       16 
## 39.86452 41.40847 38.48749 41.80721 41.58466 41.96022 40.37454 40.47190 
##       17       18       19       20       21       22       23       24 
## 41.06074 41.69130 42.40068 40.41627 41.59393 40.73155 41.37602 41.28793 
##       25       26       27       28       29       30 
## 41.59857 41.82112 42.01585 41.03756 40.46263 41.41311

##  lag Autocorrelation D-W Statistic p-value
##    1        0.112963      1.721293   0.464
##  Alternative hypothesis: rho != 0

Free Throws v wins

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.1297686
## 
## Call:
## lm(formula = W ~ FT, data = comb_team)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -24.3841  -8.1118   0.3849   8.5255  18.7619 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept) 24.71592   23.61820   1.046    0.304
## FT           0.01123    0.01622   0.693    0.494
## 
## Residual standard error: 12.14 on 28 degrees of freedom
## Multiple R-squared:  0.01684,    Adjusted R-squared:  -0.01827 
## F-statistic: 0.4796 on 1 and 28 DF,  p-value: 0.4943
##        1        2        3        4        5        6        7        8 
## 40.92362 39.11528 42.18160 41.67616 39.63195 39.78920 42.02435 39.25006 
##        9       10       11       12       13       14       15       16 
## 40.60913 39.75550 42.48486 39.29499 45.52872 39.72180 41.03594 38.62107 
##       17       18       19       20       21       22       23       24 
## 41.23812 42.35008 41.13703 41.38413 41.12580 38.54245 44.28197 40.96855 
##       25       26       27       28       29       30 
## 42.21530 39.92398 40.53050 40.99101 42.01312 41.65370

##  lag Autocorrelation D-W Statistic p-value
##    1       0.1088329       1.72528   0.442
##  Alternative hypothesis: rho != 0

Three Points v Offensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.5303433
## 
## Call:
## lm(formula = ORtg ~ x3P, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.4931 -2.1844  0.0529  2.0272  4.6598 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 98.354052   3.669782   26.80  < 2e-16 ***
## x3P          0.012927   0.003905    3.31  0.00257 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.595 on 28 degrees of freedom
## Multiple R-squared:  0.2813, Adjusted R-squared:  0.2556 
## F-statistic: 10.96 on 1 and 28 DF,  p-value: 0.002573
##        1        2        3        4        5        6        7        8 
## 112.1473 111.6949 111.8888 110.9839 107.9848 109.3033 111.5656 110.0273 
##        9       10       11       12       13       14       15       16 
## 111.1907 112.4059 115.4567 108.4243 108.9672 109.3033 108.8380 110.3504 
##       17       18       19       20       21       22       23       24 
## 112.6386 109.0448 109.2387 108.9931 110.4022 110.4668 109.8463 108.5665 
##       25       26       27       28       29       30 
## 110.0402 110.3375 108.8509 111.4751 111.1907 110.3763

##  lag Autocorrelation D-W Statistic p-value
##    1      -0.1451083      2.200583    0.61
##  Alternative hypothesis: rho != 0

Two Points v Offensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.09895804
## 
## Call:
## lm(formula = ORtg ~ x2P, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.7404 -1.9357  0.0999  2.0059  6.0050 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 1.063e+02  7.754e+00  13.714    6e-14 ***
## x2P         1.670e-03  3.174e-03   0.526    0.603    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.046 on 28 degrees of freedom
## Multiple R-squared:  0.009793,   Adjusted R-squared:  -0.02557 
## F-statistic: 0.2769 on 1 and 28 DF,  p-value: 0.6029
##        1        2        3        4        5        6        7        8 
## 110.2131 110.3701 110.0946 110.2048 110.5404 110.2415 109.9376 110.5655 
##        9       10       11       12       13       14       15       16 
## 109.9910 110.5471 109.4950 110.6907 110.6106 110.7459 110.1747 110.2098 
##       17       18       19       20       21       22       23       24 
## 110.4219 110.6490 110.9045 110.1897 110.6139 110.3033 110.5354 110.5037 
##       25       26       27       28       29       30 
## 110.6156 110.6958 110.7659 110.4135 110.2064 110.5488

##  lag Autocorrelation D-W Statistic p-value
##    1       0.0257704      1.930104    0.91
##  Alternative hypothesis: rho != 0

Free Throws v Offensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.291237
## 
## Call:
## lm(formula = ORtg ~ FT, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.1156 -1.7174  0.0868  2.2596  6.1985 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 1.013e+02  5.698e+00  17.770   <2e-16 ***
## FT          6.304e-03  3.913e-03   1.611    0.118    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.929 on 28 degrees of freedom
## Multiple R-squared:  0.08482,    Adjusted R-squared:  0.05213 
## F-statistic: 2.595 on 1 and 28 DF,  p-value: 0.1184
##        1        2        3        4        5        6        7        8 
## 110.3571 109.3422 111.0632 110.7795 109.6322 109.7205 110.9749 109.4179 
##        9       10       11       12       13       14       15       16 
## 110.1806 109.7015 111.2334 109.4431 112.9417 109.6826 110.4202 109.0649 
##       17       18       19       20       21       22       23       24 
## 110.5336 111.1577 110.4769 110.6156 110.4706 109.0207 112.2419 110.3823 
##       25       26       27       28       29       30 
## 111.0821 109.7961 110.1365 110.3950 110.9686 110.7669

##  lag Autocorrelation D-W Statistic p-value
##    1      0.04193079      1.894461   0.842
##  Alternative hypothesis: rho != 0

Three Point Percentage v Wins

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.5418599
## 
## Call:
## lm(formula = W ~ x3Pp, data = comb_team)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -21.7873  -5.8964   0.3398   7.7762  20.0635 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept)  -110.23      44.37  -2.484  0.01923 * 
## x3Pp          425.41     124.70   3.411  0.00198 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 10.29 on 28 degrees of freedom
## Multiple R-squared:  0.2936, Adjusted R-squared:  0.2684 
## F-statistic: 11.64 on 1 and 28 DF,  p-value: 0.001983
##        1        2        3        4        5        6        7        8 
## 39.51105 45.04142 39.93647 39.08564 39.08564 40.78729 34.40610 39.08564 
##        9       10       11       12       13       14       15       16 
## 37.80940 53.54969 41.21271 48.87014 54.82593 31.42820 35.25692 38.23481 
##       17       18       19       20       21       22       23       24 
## 39.93647 39.08564 36.10775 34.40610 37.80940 41.21271 42.48895 29.72655 
##       25       26       27       28       29       30 
## 42.48895 50.57180 56.52758 45.46684 41.21271 34.83151

##  lag Autocorrelation D-W Statistic p-value
##    1    -0.006206046      1.972432   0.864
##  Alternative hypothesis: rho != 0

Three Point Percentage v Offensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.5532274
## 
## Call:
## lm(formula = ORtg ~ x3Pp, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.1112 -1.8453  0.1448  1.7548  5.0457 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    71.79      11.00   6.528 4.48e-07 ***
## x3Pp          108.62      30.91   3.514  0.00152 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.55 on 28 degrees of freedom
## Multiple R-squared:  0.3061, Adjusted R-squared:  0.2813 
## F-statistic: 12.35 on 1 and 28 DF,  p-value: 0.001519
##        1        2        3        4        5        6        7        8 
## 110.0198 111.4318 110.1285 109.9112 109.9112 110.3457 108.7165 109.9112 
##        9       10       11       12       13       14       15       16 
## 109.5854 113.6042 110.4543 112.4094 113.9300 107.9562 108.9337 109.6940 
##       17       18       19       20       21       22       23       24 
## 110.1285 109.9112 109.1509 108.7165 109.5854 110.4543 110.7802 107.5217 
##       25       26       27       28       29       30 
## 110.7802 112.8438 114.3645 111.5405 110.4543 108.8251

##  lag Autocorrelation D-W Statistic p-value
##    1      -0.1190102      2.189357   0.604
##  Alternative hypothesis: rho != 0

Two Point Percentage v Wins

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.6009396
## 
## Call:
## lm(formula = W ~ x2Pp, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -23.707  -9.320   2.787   7.149  11.738 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -145.27      46.86  -3.100 0.004375 ** 
## x2Pp          358.06      90.00   3.978 0.000445 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9.785 on 28 degrees of freedom
## Multiple R-squared:  0.3611, Adjusted R-squared:  0.3383 
## F-statistic: 15.83 on 1 and 28 DF,  p-value: 0.0004453
##        1        2        3        4        5        6        7        8 
## 40.20034 43.42285 38.41006 36.26172 32.32310 29.45865 42.34868 43.42285 
##        9       10       11       12       13       14       15       16 
## 33.75533 54.16454 52.01620 39.84228 36.26172 48.43564 35.54561 36.97783 
##       17       18       19       20       21       22       23       24 
## 57.02899 35.18755 46.64536 26.23614 37.33589 36.97783 44.13896 42.70674 
##       25       26       27       28       29       30 
## 41.99062 35.18755 38.41006 47.71953 48.43564 49.15175

##  lag Autocorrelation D-W Statistic p-value
##    1    -0.006206046      1.972432   0.918
##  Alternative hypothesis: rho != 0

Two Point Percentage v Offensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.5532274
## 
## Call:
## lm(formula = ORtg ~ x2Pp, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.9585 -1.4956  0.1481  1.8522  4.0339 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    60.36      11.20   5.391 9.52e-06 ***
## x2Pp           96.19      21.50   4.473 0.000117 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.338 on 28 degrees of freedom
## Multiple R-squared:  0.4168, Adjusted R-squared:  0.3959 
## F-statistic: 20.01 on 1 and 28 DF,  p-value: 0.0001169
##        1        2        3        4        5        6        7        8 
## 110.1852 111.0509 109.7042 109.1271 108.0690 107.2995 110.7623 111.0509 
##        9       10       11       12       13       14       15       16 
## 108.4538 113.9366 113.3594 110.0890 109.1271 112.3975 108.9347 109.3195 
##       17       18       19       20       21       22       23       24 
## 114.7061 108.8385 111.9166 106.4338 109.4157 109.3195 111.2433 110.8585 
##       25       26       27       28       29       30 
## 110.6661 108.8385 109.7042 112.2052 112.3975 112.5899

##  lag Autocorrelation D-W Statistic p-value
##    1      -0.1360498      2.229185    0.58
##  Alternative hypothesis: rho != 0

Free Throw Percentage v Wins

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.1611608
## 
## Call:
## lm(formula = W ~ FTp, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -23.520  -7.355   1.762   9.610  18.637 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)    -5.18      53.49  -0.097    0.924
## FTp            60.21      69.68   0.864    0.395
## 
## Residual standard error: 12.08 on 28 degrees of freedom
## Multiple R-squared:  0.02597,    Adjusted R-squared:  -0.008814 
## F-statistic: 0.7466 on 1 and 28 DF,  p-value: 0.3949
##        1        2        3        4        5        6        7        8 
## 40.09884 43.10939 39.67737 42.80834 41.96538 42.50728 39.49673 40.27948 
##        9       10       11       12       13       14       15       16 
## 39.79779 43.04918 42.44707 40.09884 42.50728 36.90766 41.30306 36.66682 
##       17       18       19       20       21       22       23       24 
## 41.36327 42.20623 40.64074 40.52032 37.75061 41.90517 41.24285 41.72454 
##       25       26       27       28       29       30 
## 43.83192 38.53336 44.13298 43.22981 39.13547 41.06222

##  lag Autocorrelation D-W Statistic p-value
##    1       0.1036315      1.742503   0.504
##  Alternative hypothesis: rho != 0

Free Throw Percentage v Offensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.4243103
## 
## Call:
## lm(formula = ORtg ~ FTp, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.2356 -0.5181  0.3085  1.7017  4.1508 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    80.00      12.27   6.518 4.59e-07 ***
## FTp            39.64      15.99   2.480   0.0194 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.772 on 28 degrees of freedom
## Multiple R-squared:   0.18,  Adjusted R-squared:  0.1508 
## F-statistic: 6.148 on 1 and 28 DF,  p-value: 0.01944
##        1        2        3        4        5        6        7        8 
## 109.8067 111.7888 109.5292 111.5906 111.0356 111.3924 109.4103 109.9256 
##        9       10       11       12       13       14       15       16 
## 109.6085 111.7492 111.3527 109.8067 111.3924 107.7056 110.5995 107.5470 
##       17       18       19       20       21       22       23       24 
## 110.6392 111.1942 110.1635 110.0842 108.2606 110.9960 110.5599 110.8770 
##       25       26       27       28       29       30 
## 112.2645 108.7760 112.4627 111.8681 109.1724 110.4410

##  lag Autocorrelation D-W Statistic p-value
##    1     -0.01352301       2.01149    0.91
##  Alternative hypothesis: rho != 0

Offensive Rebounds v Offensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.117081
## 
## Call:
## lm(formula = ORtg ~ ORB, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9373 -2.3514  0.2509  2.0480  5.7247 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 1.067e+02  5.964e+00  17.891   <2e-16 ***
## ORB         4.366e-03  6.998e-03   0.624    0.538    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.04 on 28 degrees of freedom
## Multiple R-squared:  0.01371,    Adjusted R-squared:  -0.02152 
## F-statistic: 0.3892 on 1 and 28 DF,  p-value: 0.5378
##        1        2        3        4        5        6        7        8 
## 110.8651 110.2059 110.6250 110.2495 109.8304 110.5333 110.3281 110.9393 
##        9       10       11       12       13       14       15       16 
## 110.7822 110.1753 110.3456 110.0225 110.1709 110.3412 109.8522 110.7167 
##       17       18       19       20       21       22       23       24 
## 110.0225 110.7254 110.6643 110.4373 111.1969 110.2845 110.5901 109.9614 
##       25       26       27       28       29       30 
## 110.9175 110.6512 110.0007 110.1273 110.2757 110.1622

##  lag Autocorrelation D-W Statistic p-value
##    1      0.02811017      1.910839   0.804
##  Alternative hypothesis: rho != 0

Defensive Rebounds v Defensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] -0.5825676
## 
## Call:
## lm(formula = DRtg ~ DRB, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.9317 -2.4715  0.6419  1.4557  4.4717 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 143.355591   8.699642  16.478 6.08e-16 ***
## DRB          -0.011542   0.003043  -3.793  0.00073 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.434 on 28 degrees of freedom
## Multiple R-squared:  0.3394, Adjusted R-squared:  0.3158 
## F-statistic: 14.38 on 1 and 28 DF,  p-value: 0.0007305
##        1        2        3        4        5        6        7        8 
## 110.7507 110.4737 109.6658 111.2932 111.0508 113.1283 110.0698 110.6699 
##        9       10       11       12       13       14       15       16 
## 111.5933 108.8464 113.1975 111.4317 109.4696 108.9041 112.1588 110.1275 
##       17       18       19       20       21       22       23       24 
## 105.0838 111.6163 109.0888 110.9123 109.7582 109.8620 108.4424 113.7746 
##       25       26       27       28       29       30 
## 109.1003 110.8200 109.7697 109.6543 108.9503 112.4358

##  lag Autocorrelation D-W Statistic p-value
##    1       0.1855995       1.55609   0.222
##  Alternative hypothesis: rho != 0

Steals v Defensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] -0.2123928
## 
## Call:
## lm(formula = DRtg ~ STL, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.3024 -1.8397 -0.6048  1.9845  6.3658 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 116.058784   4.946220   23.46   <2e-16 ***
## STL          -0.009035   0.007855   -1.15     0.26    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.926 on 28 degrees of freedom
## Multiple R-squared:  0.04511,    Adjusted R-squared:  0.01101 
## F-statistic: 1.323 on 1 and 28 DF,  p-value: 0.2598
##        1        2        3        4        5        6        7        8 
## 109.9603 109.6803 111.1891 110.7192 110.6108 111.2342 111.2433 110.3308 
##        9       10       11       12       13       14       15       16 
## 110.9180 110.4121 109.7345 109.6170 110.9903 110.4753 109.8790 110.3940 
##       17       18       19       20       21       22       23       24 
## 110.5024 109.8881 110.5476 111.0264 109.1382 111.1529 110.5837 109.4182 
##       25       26       27       28       29       30 
## 111.1258 109.9242 111.5324 109.9152 110.0687 109.8881

##  lag Autocorrelation D-W Statistic p-value
##    1      0.05713453      1.753875   0.514
##  Alternative hypothesis: rho != 0

Steals v Offensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.02283556
## 
## Call:
## lm(formula = ORtg ~ STL, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.8315 -2.1159  0.2053  2.1810  5.5010 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 1.098e+02  5.173e+00  21.222   <2e-16 ***
## STL         9.930e-04  8.216e-03   0.121    0.905    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.06 on 28 degrees of freedom
## Multiple R-squared:  0.0005215,  Adjusted R-squared:  -0.03517 
## F-statistic: 0.01461 on 1 and 28 DF,  p-value: 0.9047
##        1        2        3        4        5        6        7        8 
## 110.4487 110.4795 110.3136 110.3653 110.3772 110.3087 110.3077 110.4080 
##        9       10       11       12       13       14       15       16 
## 110.3434 110.3990 110.4735 110.4864 110.3355 110.3921 110.4576 110.4010 
##       17       18       19       20       21       22       23       24 
## 110.3891 110.4566 110.3841 110.3315 110.5390 110.3176 110.3802 110.5083 
##       25       26       27       28       29       30 
## 110.3206 110.4527 110.2759 110.4537 110.4368 110.4566

##  lag Autocorrelation D-W Statistic p-value
##    1    -0.004529181      1.986446   0.994
##  Alternative hypothesis: rho != 0

Assists v Offensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] 0.459058
## 
## Call:
## lm(formula = ORtg ~ AST, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.0234 -1.9528 -0.1719  1.6681  7.3184 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 94.142343   5.966670  15.778 1.83e-15 ***
## AST          0.008064   0.002949   2.734   0.0107 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.72 on 28 degrees of freedom
## Multiple R-squared:  0.2107, Adjusted R-squared:  0.1825 
## F-statistic: 7.476 on 1 and 28 DF,  p-value: 0.01072
##        1        2        3        4        5        6        7        8 
## 111.2217 111.5201 109.8992 109.5041 108.6251 107.8349 109.6089 112.2458 
##        9       10       11       12       13       14       15       16 
## 109.0203 113.6006 108.1816 111.3024 110.0283 111.0443 109.9718 110.1976 
##       17       18       19       20       21       22       23       24 
## 111.3669 110.4153 112.0120 107.4155 109.6009 111.0362 111.9394 109.9234 
##       25       26       27       28       29       30 
## 109.3589 110.9395 110.3750 110.9556 111.3427 111.5120
##            1            2            3            4            5            6 
## -1.174898870  0.257314183 -0.112169486  0.714410886 -1.474630626 -0.053862080 
##            7            8            9           10           11           12 
## -0.078596860  0.291486225 -0.007717094  0.956454765  2.872334280 -0.528490669 
##           13           14           15           16           17           18 
##  0.888131948 -1.218041295 -1.450463592 -1.084055199  0.918004517  0.368249824 
##           19           20           21           22           23           24 
## -0.234640457 -1.194395319  0.263037313 -0.801952132  0.252715357 -1.507882164 
##           25           26           27           28           29           30 
##  2.018003162 -0.202304074  0.944301567  0.804284748 -0.166943297 -0.155898246

##  lag Autocorrelation D-W Statistic p-value
##    1       -0.109389      2.170904   0.652
##  Alternative hypothesis: rho != 0

Blocks v Defensive Rating

## `geom_smooth()` using formula 'y ~ x'

## [1] -0.561718
## 
## Call:
## lm(formula = DRtg ~ BLK, data = comb_team)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.9633 -2.2885  0.1359  1.8858  5.0243 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 121.648806   3.162619  38.465  < 2e-16 ***
## BLK          -0.027687   0.007706  -3.593  0.00124 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.478 on 28 degrees of freedom
## Multiple R-squared:  0.3155, Adjusted R-squared:  0.2911 
## F-statistic: 12.91 on 1 and 28 DF,  p-value: 0.001238
##        1        2        3        4        5        6        7        8 
## 110.0480 109.6050 112.2630 110.4356 111.9307 116.2499 111.9307 111.5985 
##        9       10       11       12       13       14       15       16 
## 112.4845 107.1132 110.4356 110.4633 110.9894 109.4666 109.2451 109.2451 
##       17       18       19       20       21       22       23       24 
## 108.1930 110.2695 109.4389 109.9650 109.8819 109.3282 109.6881 110.0757 
##       25       26       27       28       29       30 
## 110.2141 111.5985 110.9617 109.5497 108.2761 111.1555

##  lag Autocorrelation D-W Statistic p-value
##    1       0.0515884      1.766672   0.478
##  Alternative hypothesis: rho != 0

Five Summary Statistics

##     avg_3p     s_3p avg_ptspg  s_ptspg         r
## 1 11.36382 1.504955  111.2085 4.092142 0.4565562
##     avg_2p     s_2p avg_ptspg  s_ptspg         r
## 1 29.71829 2.173743  111.2085 4.092142 0.3105844
##     avg_ft     s_ft avg_ptspg  s_ptspg         r
## 1 17.68049 1.694804  111.2085 4.092142 0.4015758
##    avg_ast   s_ast avg_ptspg  s_ptspg         r
## 1 24.58659 2.08829  111.2085 4.092142 0.5653053
##   avg_stl     s_stl avg_ptspg  s_ptspg        r
## 1 7.63374 0.8436119  111.2085 4.092142 0.171338
##    avg_orb     s_orb avg_ptspg  s_ptspg         r
## 1 10.34715 0.9837691  111.2085 4.092142 0.1915307
##    avg_drb    s_drb avg_ptspg  s_ptspg         r
## 1 34.81829 1.811346  111.2085 4.092142 0.5642984

Regression Lines

Point Guard

Shooting Guard

Small Forward

Power Forward

Centres

Position specific five summary statistics

Point Guard

Shooting Guard

Small Forward

Power Forward

Centres

Regression Lines

Point Guards

Shooting Guard

Small Forwards

Centres

Linear Modelling For PLayers

Combined Players

## # A tibble: 5 x 7
##   term         estimate  std.error statistic   p.value  conf.low conf.high
##   <chr>           <dbl>      <dbl>     <dbl>     <dbl>     <dbl>     <dbl>
## 1 (Intercept)  0.382    0.00622        61.4  2.80e-198  0.370     0.394   
## 2 MP          -0.000187 0.00000924    -20.2  4.18e- 62 -0.000205 -0.000169
## 3 x3P          0.00140  0.0000778      18.0  9.47e- 53  0.00125   0.00155 
## 4 x2P          0.00105  0.0000538      19.6  1.97e- 59  0.000948  0.00116 
## 5 FT           0.000319 0.0000594       5.37 1.42e-  7  0.000202  0.000435
## # A tibble: 5 x 7
##   term        estimate std.error statistic  p.value conf.low conf.high
##   <chr>          <dbl>     <dbl>     <dbl>    <dbl>    <dbl>     <dbl>
## 1 (Intercept)   6.63     0.253       26.2  5.24e-87   6.13      7.12  
## 2 G            -0.100    0.00542    -18.5  8.34e-55  -0.111    -0.0896
## 3 x3P           0.0427   0.00150     28.4  8.04e-96   0.0397    0.0456
## 4 x2P           0.0297   0.00106     27.9  7.56e-94   0.0276    0.0317
## 5 FT            0.0136   0.00146      9.31 1.09e-18   0.0107    0.0165
## # A tibble: 6 x 7
##   term        estimate std.error statistic  p.value conf.low conf.high
##   <chr>          <dbl>     <dbl>     <dbl>    <dbl>    <dbl>     <dbl>
## 1 (Intercept)   40.0      18.5        2.16 3.12e- 2    3.63    76.3   
## 2 AST           -0.272     0.181     -1.50 1.34e- 1   -0.627    0.0842
## 3 DRB            0.842     0.166      5.09 5.80e- 7    0.517    1.17  
## 4 ORB           -0.632     0.315     -2.00 4.58e- 2   -1.25    -0.0119
## 5 BLK            0.533     0.524      1.02 3.10e- 1   -0.498    1.56  
## 6 TOV            6.33      0.463     13.7  8.22e-35    5.42     7.24

Point Guard

## # A tibble: 5 x 7
##   term         estimate std.error statistic  p.value   conf.low conf.high
##   <chr>           <dbl>     <dbl>     <dbl>    <dbl>      <dbl>     <dbl>
## 1 (Intercept)  0.363    0.0142        25.4  1.23e-38  0.334      0.391   
## 2 MP          -0.000162 0.0000196     -8.29 3.41e-12 -0.000201  -0.000123
## 3 x3P          0.00125  0.000150       8.33 2.83e-12  0.000952   0.00155 
## 4 x2P          0.00102  0.000112       9.13 8.48e-14  0.000800   0.00125 
## 5 FT           0.000264 0.000107       2.47 1.56e- 2  0.0000514  0.000477
## # A tibble: 5 x 7
##   term        estimate std.error statistic  p.value conf.low conf.high
##   <chr>          <dbl>     <dbl>     <dbl>    <dbl>    <dbl>     <dbl>
## 1 (Intercept)  7.10      0.630       11.3  8.59e-18  5.85       8.36  
## 2 G           -0.106     0.0136      -7.80 2.90e-11 -0.133     -0.0790
## 3 x3P          0.0423    0.00397     10.6  1.20e-16  0.0344     0.0502
## 4 x2P          0.0318    0.00252     12.7  2.70e-20  0.0268     0.0368
## 5 FT           0.00954   0.00306      3.11 2.61e- 3  0.00344    0.0156
## # A tibble: 6 x 7
##   term        estimate std.error statistic      p.value conf.low conf.high
##   <chr>          <dbl>     <dbl>     <dbl>        <dbl>    <dbl>     <dbl>
## 1 (Intercept)   17.0      50.1       0.339 0.735         -82.8      117.  
## 2 AST            0.228     0.430     0.530 0.598          -0.628      1.08
## 3 DRB            0.152     0.616     0.246 0.806          -1.08       1.38
## 4 ORB           -1.15      2.11     -0.543 0.589          -5.36       3.06
## 5 BLK            2.85      3.12      0.911 0.365          -3.38       9.07
## 6 TOV            5.78      0.917     6.30  0.0000000191    3.95       7.61

Shooting Guard

## # A tibble: 5 x 7
##   term         estimate std.error statistic  p.value  conf.low conf.high
##   <chr>           <dbl>     <dbl>     <dbl>    <dbl>     <dbl>     <dbl>
## 1 (Intercept)  0.376    0.0119        31.6  1.77e-49  0.353     0.400   
## 2 MP          -0.000173 0.0000181     -9.56 3.19e-15 -0.000210 -0.000137
## 3 x3P          0.00145  0.000160       9.04 3.76e-14  0.00113   0.00177 
## 4 x2P          0.000842 0.000112       7.51 4.78e-11  0.000619  0.00107 
## 5 FT           0.000494 0.000154       3.21 1.87e- 3  0.000188  0.000800
## # A tibble: 5 x 7
##   term        estimate std.error statistic  p.value conf.low conf.high
##   <chr>          <dbl>     <dbl>     <dbl>    <dbl>    <dbl>     <dbl>
## 1 (Intercept)   5.87     0.486       12.1  2.84e-20   4.90      6.83  
## 2 G            -0.0860   0.0109      -7.86 9.58e-12  -0.108    -0.0643
## 3 x3P           0.0428   0.00312     13.7  1.96e-23   0.0365    0.0490
## 4 x2P           0.0253   0.00258      9.82 9.48e-16   0.0202    0.0304
## 5 FT            0.0190   0.00382      4.98 3.13e- 6   0.0115    0.0266
## # A tibble: 6 x 7
##   term        estimate std.error statistic    p.value conf.low conf.high
##   <chr>          <dbl>     <dbl>     <dbl>      <dbl>    <dbl>     <dbl>
## 1 (Intercept)  -13.8      38.5      -0.359 0.720       -90.4       62.7 
## 2 AST            0.246     0.474     0.519 0.605        -0.696      1.19
## 3 DRB            2.20      0.462     4.76  0.00000781    1.28       3.11
## 4 ORB            1.99      1.46      1.36  0.177        -0.912      4.88
## 5 BLK           -3.29      2.20     -1.49  0.139        -7.67       1.09
## 6 TOV            4.32      0.946     4.56  0.0000167     2.44       6.20

Small Forward

## # A tibble: 5 x 7
##   term         estimate std.error statistic  p.value   conf.low conf.high
##   <chr>           <dbl>     <dbl>     <dbl>    <dbl>      <dbl>     <dbl>
## 1 (Intercept)  0.346    0.0119        29.0  1.25e-34  0.322      0.370   
## 2 MP          -0.000163 0.0000192     -8.49 1.63e-11 -0.000201  -0.000124
## 3 x3P          0.00131  0.000230       5.69 5.36e- 7  0.000848   0.00177 
## 4 x2P          0.00106  0.000132       8.03 8.68e-11  0.000794   0.00132 
## 5 FT           0.000294 0.000152       1.94 5.82e- 2 -0.0000106  0.000600
## # A tibble: 5 x 7
##   term        estimate std.error statistic  p.value  conf.low conf.high
##   <chr>          <dbl>     <dbl>     <dbl>    <dbl>     <dbl>     <dbl>
## 1 (Intercept)  7.34      0.569       12.9  4.05e-18  6.20        8.48  
## 2 G           -0.117     0.0125      -9.36 6.69e-13 -0.143      -0.0923
## 3 x3P          0.0438    0.00535      8.18 5.03e-11  0.0331      0.0545
## 4 x2P          0.0364    0.00335     10.9  3.37e-15  0.0296      0.0431
## 5 FT           0.00819   0.00456      1.80 7.79e- 2 -0.000946    0.0173
## # A tibble: 6 x 7
##   term        estimate std.error statistic   p.value conf.low conf.high
##   <chr>          <dbl>     <dbl>     <dbl>     <dbl>    <dbl>     <dbl>
## 1 (Intercept)  -73.4      43.6      -1.68  0.0982    -161.       14.1  
## 2 AST           -0.642     0.532    -1.21  0.233       -1.71      0.425
## 3 DRB            1.77      0.504     3.51  0.000920     0.758     2.78 
## 4 ORB           -0.497     1.06     -0.468 0.642       -2.63      1.63 
## 5 BLK            0.833     1.58      0.528 0.600       -2.33      4.00 
## 6 TOV            6.12      1.31      4.67  0.0000212    3.49      8.75

Power Forward

## # A tibble: 5 x 7
##   term         estimate std.error statistic  p.value  conf.low conf.high
##   <chr>           <dbl>     <dbl>     <dbl>    <dbl>     <dbl>     <dbl>
## 1 (Intercept)  0.413    0.0177        23.4  3.03e-34  0.378     0.448   
## 2 MP          -0.000246 0.0000345     -7.13 8.41e-10 -0.000314 -0.000177
## 3 x3P          0.00184  0.000395       4.66 1.54e- 5  0.00105   0.00263 
## 4 x2P          0.00125  0.000207       6.06 6.79e- 8  0.000840  0.00167 
## 5 FT           0.000295 0.000238       1.24 2.19e- 1 -0.000179  0.000770
## # A tibble: 5 x 7
##   term        estimate std.error statistic  p.value conf.low conf.high
##   <chr>          <dbl>     <dbl>     <dbl>    <dbl>    <dbl>     <dbl>
## 1 (Intercept)   6.24     0.641        9.74 1.61e-14  4.96       7.52  
## 2 G            -0.101    0.0155      -6.51 1.07e- 8 -0.132     -0.0700
## 3 x3P           0.0479   0.00564      8.49 2.79e-12  0.0366     0.0592
## 4 x2P           0.0288   0.00314      9.16 1.74e-13  0.0225     0.0351
## 5 FT            0.0152   0.00454      3.34 1.35e- 3  0.00612    0.0242
## # A tibble: 6 x 7
##   term        estimate std.error statistic  p.value conf.low conf.high
##   <chr>          <dbl>     <dbl>     <dbl>    <dbl>    <dbl>     <dbl>
## 1 (Intercept) -23.2       30.1     -0.772  4.43e- 1  -83.3      36.8  
## 2 AST          -1.51       0.395   -3.83   2.81e- 4   -2.30     -0.725
## 3 DRB           1.25       0.257    4.88   6.96e- 6    0.741     1.77 
## 4 ORB           0.0810     0.544    0.149  8.82e- 1   -1.01      1.17 
## 5 BLK           0.0720     0.929    0.0775 9.38e- 1   -1.78      1.93 
## 6 TOV           6.74       0.910    7.40   2.84e-10    4.92      8.55

Centres

## # A tibble: 5 x 7
##   term         estimate std.error statistic  p.value  conf.low conf.high
##   <chr>           <dbl>     <dbl>     <dbl>    <dbl>     <dbl>     <dbl>
## 1 (Intercept)  0.400    0.0122        32.8  3.56e-42  0.376     0.425   
## 2 MP          -0.000225 0.0000210    -10.7  4.89e-16 -0.000267 -0.000183
## 3 x3P          0.00175  0.000198       8.82 1.03e-12  0.00135   0.00214 
## 4 x2P          0.00116  0.000107      10.8  3.19e-16  0.000947  0.00137 
## 5 FT           0.000367 0.000108       3.38 1.22e- 3  0.000150  0.000584
## # A tibble: 5 x 7
##   term        estimate std.error statistic  p.value conf.low conf.high
##   <chr>          <dbl>     <dbl>     <dbl>    <dbl>    <dbl>     <dbl>
## 1 (Intercept)   7.35     0.568       12.9  1.17e-19   6.22      8.49  
## 2 G            -0.115    0.0116      -9.90 1.31e-14  -0.138    -0.0919
## 3 x3P           0.0433   0.00452      9.58 4.77e-14   0.0343    0.0524
## 4 x2P           0.0282   0.00192     14.7  2.13e-22   0.0244    0.0321
## 5 FT            0.0177   0.00286      6.20 4.36e- 8   0.0120    0.0234
## # A tibble: 6 x 7
##   term        estimate std.error statistic    p.value  conf.low conf.high
##   <chr>          <dbl>     <dbl>     <dbl>      <dbl>     <dbl>     <dbl>
## 1 (Intercept) -58.3       36.8     -1.58   0.118      -132.        15.3  
## 2 AST           0.662      0.455    1.46   0.150        -0.246      1.57 
## 3 DRB           0.0150     0.269    0.0556 0.956        -0.523      0.552
## 4 ORB           0.654      0.367    1.78   0.0798       -0.0798     1.39 
## 5 BLK           2.44       0.534    4.57   0.0000231     1.37       3.50 
## 6 TOV           5.06       0.982    5.16   0.00000264    3.10       7.03

Adding Salary values

Point Guard

Shooting Guard

Small Forward

Power Forward

Centres

Selected Team

## # A tibble: 5 x 40
## # Groups:   Pos [5]
##   player_name Pos     Age Tm    Salary     G    GS    MP    FG   FGA   FGp   x3P
##   <chr>       <chr> <dbl> <chr>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Karl-Antho… C        23 MIN   7.84e6    77    77  2545   681  1314 0.518   142
## 2 Tobias Har… PF       26 TOT   1.48e7    82    82  2847   611  1254 0.487   156
## 3 Kevin Dura… SF       30 GSW   3.00e7    78    78  2702   721  1383 0.521   137
## 4 Donovan Mi… SG       22 UTA   3.11e6    77    77  2598   661  1530 0.432   188
## 5 D'Angelo R… PG       22 BRK   7.02e6    81    81  2448   659  1517 0.434   234
## # … with 28 more variables: x3PA <dbl>, x3Pp <dbl>, x2P <dbl>, x2PA <dbl>,
## #   x2Pp <dbl>, eFGp <dbl>, FT <dbl>, FTA <dbl>, FTp <dbl>, ORB <dbl>,
## #   DRB <dbl>, TRB <dbl>, AST <dbl>, STL <dbl>, BLK <dbl>, TOV <dbl>, PF <dbl>,
## #   PTS <dbl>, PTSpm <dbl>, FTpm <dbl>, BLKpm <dbl>, ASTpm <dbl>, STLpm <dbl>,
## #   TOVpm <dbl>, x3Ppm <dbl>, PPG <dbl>, APG <dbl>, RPG <dbl>